Subjects -> MATHEMATICS (Total: 1013 journals)
    - APPLIED MATHEMATICS (92 journals)
    - GEOMETRY AND TOPOLOGY (23 journals)
    - MATHEMATICS (714 journals)
    - MATHEMATICS (GENERAL) (45 journals)
    - NUMERICAL ANALYSIS (26 journals)
    - PROBABILITIES AND MATH STATISTICS (113 journals)

PROBABILITIES AND MATH STATISTICS (113 journals)                     

Showing 1 - 98 of 98 Journals sorted alphabetically
Advances in Statistics     Open Access   (Followers: 10)
Afrika Statistika     Open Access   (Followers: 1)
American Journal of Applied Mathematics and Statistics     Open Access   (Followers: 13)
American Journal of Mathematics and Statistics     Open Access   (Followers: 9)
Annals of Data Science     Hybrid Journal   (Followers: 15)
Annual Review of Statistics and Its Application     Full-text available via subscription   (Followers: 11)
Applied Medical Informatics     Open Access   (Followers: 12)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Asian Journal of Probability and Statistics     Open Access  
Austrian Journal of Statistics     Open Access   (Followers: 4)
Biostatistics & Epidemiology     Hybrid Journal   (Followers: 6)
Cadernos do IME : Série Estatística     Open Access  
Calcutta Statistical Association Bulletin     Hybrid Journal  
Communications in Mathematics and Statistics     Hybrid Journal   (Followers: 3)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics: Case Studies, Data Analysis and Applications     Hybrid Journal  
Comunicaciones en Estadística     Open Access  
Econometrics and Statistics     Hybrid Journal   (Followers: 2)
Forecasting     Open Access   (Followers: 1)
Foundations and Trends® in Optimization     Full-text available via subscription   (Followers: 2)
Frontiers in Applied Mathematics and Statistics     Open Access   (Followers: 2)
Game Theory     Open Access   (Followers: 2)
Geoinformatics & Geostatistics     Hybrid Journal   (Followers: 10)
Geomatics, Natural Hazards and Risk     Open Access   (Followers: 14)
Indonesian Journal of Applied Statistics     Open Access  
International Game Theory Review     Hybrid Journal  
International Journal of Advanced Statistics and IT&C for Economics and Life Sciences     Open Access  
International Journal of Advanced Statistics and Probability     Open Access   (Followers: 7)
International Journal of Algebra and Statistics     Open Access   (Followers: 4)
International Journal of Applied Mathematics and Statistics     Full-text available via subscription   (Followers: 4)
International Journal of Ecological Economics and Statistics     Full-text available via subscription   (Followers: 4)
International Journal of Energy and Statistics     Hybrid Journal   (Followers: 4)
International Journal of Game Theory     Hybrid Journal   (Followers: 3)
International Journal of Mathematics and Statistics     Full-text available via subscription   (Followers: 2)
International Journal of Multivariate Data Analysis     Hybrid Journal  
International Journal of Probability and Statistics     Open Access   (Followers: 3)
International Journal of Statistics & Economics     Full-text available via subscription   (Followers: 6)
International Journal of Statistics and Applications     Open Access   (Followers: 2)
International Journal of Statistics and Probability     Open Access   (Followers: 3)
International Journal of Statistics in Medical Research     Hybrid Journal   (Followers: 2)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Iraqi Journal of Statistical Sciences     Open Access  
Japanese Journal of Statistics and Data Science     Hybrid Journal  
Journal of Biometrics & Biostatistics     Open Access   (Followers: 4)
Journal of Cost Analysis and Parametrics     Hybrid Journal   (Followers: 5)
Journal of Environmental Statistics     Open Access   (Followers: 4)
Journal of Game Theory     Open Access   (Followers: 1)
Journal of Mathematical Economics and Finance     Full-text available via subscription  
Journal of Mathematics and Statistics Studies     Open Access  
Journal of Modern Applied Statistical Methods     Open Access   (Followers: 1)
Journal of Official Statistics     Open Access   (Followers: 2)
Journal of Quantitative Economics     Hybrid Journal  
Journal of Social and Economic Statistics     Open Access   (Followers: 4)
Journal of Statistical Theory and Practice     Hybrid Journal   (Followers: 2)
Journal of Statistics and Data Science Education     Open Access   (Followers: 2)
Journal of Survey Statistics and Methodology     Hybrid Journal   (Followers: 6)
Journal of the Indian Society for Probability and Statistics     Full-text available via subscription  
Jurnal Biometrika dan Kependudukan     Open Access   (Followers: 1)
Jurnal Ekonomi Kuantitatif Terapan     Open Access  
Jurnal Sains Matematika dan Statistika     Open Access  
Lietuvos Statistikos Darbai     Open Access   (Followers: 1)
Mathematics and Statistics     Open Access   (Followers: 2)
Methods, Data, Analyses     Open Access   (Followers: 1)
METRON     Hybrid Journal   (Followers: 2)
Nepalese Journal of Statistics     Open Access   (Followers: 1)
North American Actuarial Journal     Hybrid Journal   (Followers: 2)
Open Journal of Statistics     Open Access   (Followers: 3)
Open Mathematics, Statistics and Probability Journal     Open Access  
Pakistan Journal of Statistics and Operation Research     Open Access   (Followers: 1)
Physica A: Statistical Mechanics and its Applications     Hybrid Journal   (Followers: 7)
Probability, Uncertainty and Quantitative Risk     Open Access   (Followers: 2)
Ratio Mathematica     Open Access  
Research & Reviews : Journal of Statistics     Open Access   (Followers: 4)
Revista Brasileira de Biometria     Open Access  
Revista Colombiana de Estadística     Open Access  
RMS : Research in Mathematics & Statistics     Open Access   (Followers: 1)
Romanian Statistical Review     Open Access  
Sankhya B - Applied and Interdisciplinary Statistics     Hybrid Journal  
SIAM Journal on Mathematics of Data Science     Hybrid Journal   (Followers: 6)
SIAM/ASA Journal on Uncertainty Quantification     Hybrid Journal   (Followers: 3)
Spatial Statistics     Hybrid Journal   (Followers: 2)
Sri Lankan Journal of Applied Statistics     Open Access  
Stat     Hybrid Journal   (Followers: 1)
Stata Journal     Full-text available via subscription   (Followers: 9)
Statistica     Open Access   (Followers: 6)
Statistical Analysis and Data Mining     Hybrid Journal   (Followers: 23)
Statistical Theory and Related Fields     Hybrid Journal  
Statistics and Public Policy     Open Access   (Followers: 3)
Statistics in Transition New Series : An International Journal of the Polish Statistical Association     Open Access  
Statistics Research Letters     Open Access   (Followers: 1)
Statistics, Optimization & Information Computing     Open Access   (Followers: 5)
Stats     Open Access  
Synthesis Lectures on Mathematics and Statistics     Full-text available via subscription   (Followers: 1)
Theory of Probability and its Applications     Hybrid Journal   (Followers: 2)
Theory of Probability and Mathematical Statistics     Full-text available via subscription   (Followers: 2)
Turkish Journal of Forecasting     Open Access   (Followers: 1)
VARIANSI : Journal of Statistics and Its application on Teaching and Research     Open Access   (Followers: 4)
Zeitschrift für die gesamte Versicherungswissenschaft     Hybrid Journal  

           

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Journal Cover
Sankhya B - Applied and Interdisciplinary Statistics
Journal Prestige (SJR): 0.1
Number of Followers: 0  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0976-8386 - ISSN (Online) 0976-8394
Published by Springer-Verlag Homepage  [2468 journals]
  • Estimation of Domain Mean Using General Class of Imputation Methods

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      Abstract: Abstract Small area estimation (SAE) approach has been employed to produce realistic estimates for the variable of interest in cases when the available data are insufficient to produce reliable estimates for the domain. Missing data is a significant issue that affects sample surveys, but in case of SAE, it is particularly vulnerable. To overcome the problem of missing data in case of SAE, this study is a fundamental effort that proposes some general imputation methods for the domain mean estimation under simple random sampling. The mean square error expressions of the proposed imputation methods are determined up to first order approximation. The analytical study is carried out to establish the efficiency conditions. A simulation analysis is performed by utilizing hypothetically created data sets. Further, the simulation analysis is extended with a real data application. In addition, appropriate recommendations for practical applications have been provided to survey experts.
      PubDate: 2024-06-03
       
  • The Extended Bregman Divergence and Parametric Estimation in Continuous
           Models

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      Abstract: Abstract Under standard regularity conditions, the maximum likelihood estimator (MLE) is the most efficient estimator at the model. However, modern practice recognizes that it is rare for the hypothesized model to hold exactly, and small departures from it are never entirely unexpected. But classical estimators like the MLE are extremely sensitive to the presence of noise in the data. Within the class of robust estimators, which constitutes parametric inference techniques designed to overcome the problems due to model misspecification and noise, minimum distance estimators have become quite popular in recent times. In particular, density-based distances under the umbrella of the Bregman divergence have been demonstrated to have several advantages. Here we will consider an extension of the ordinary Bregman divergence, and investigate the scope of parametric estimation under continuous models using this extended divergence proposal. Many of our illustrations will be based on the GSB divergence, a particular member of the extended Bregman divergence, which appears to hold high promise within the robustness area. To establish the usefulness of the proposed minimum distance estimation procedure, we will provide detailed theoretical investigations followed by substantial numerical verifications.
      PubDate: 2024-05-17
       
  • Word Embeddings as Statistical Estimators

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      Abstract: Abstract Word embeddings are a fundamental tool in natural language processing. Currently, word embedding methods are evaluated on the basis of empirical performance on benchmark data sets, and there is a lack of rigorous understanding of their theoretical properties. This paper studies word embeddings from a statistical theoretical perspective, which is essential for formal inference and uncertainty quantification. We propose a copula-based statistical model for text data and show that under this model, the now-classical Word2Vec method can be interpreted as a statistical estimation method for estimating the theoretical pointwise mutual information (PMI). We further illustrate the utility of this statistical model by using it to develop a missing value-based estimator as a statistically tractable and interpretable alternative to the Word2Vec approach. The estimation error of this estimator is comparable to Word2Vec and improves upon the truncation-based method proposed by Levy and Goldberg (Adv. Neural Inf. Process. Syst., 27, 2177–2185 2014). The resulting estimator also is comparable to Word2Vec in a benchmark sentiment analysis task on the IMDb Movie Reviews data set and a part-of-speech tagging task on the OntoNotes data set.
      PubDate: 2024-05-09
       
  • Improved Test Procedure and Sample Size Calculation for Assessing
           Similarity in Two-Group Comparative Studies with Heterogeneous Variances

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      Abstract: Abstract The two one-sided tests (TOST) method for mean equivalence or average equivalence has been extended to assessing similarity or switchability for individual equivalence in clinical trials. Tolerance interval procedures are available to establish similarity with respect to the proportion of the response differences covered by a prespecified threshold range. However, the extended TOST procedures based on tolerance intervals are potentially susceptible to the control of Type I errors. This article aims to present an exact approach with the specified Type I error probability for appraising similarity between two treatments in comparative studies with heterogeneous variances. Analytic examination and numerical comparison are conducted to clarify the utility of the suggested similarity test and the drawback of the current TOST procedures. To enhance the usefulness of the described exact method, the related power and sample size issues are also considered. Computer algorithms are provided to implement the proposed test procedure, power calculation, and sample size determination in similarity studies.
      PubDate: 2024-05-08
       
  • Inference for A Generalized Family of Distributions Under Partially
           Observed Left Truncated and Right Censored Competing Risks Data

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      Abstract: Abstract We make inference for a competing risks model under the assumption that observations are left-truncated and right-censored and failure causes are partially observed. When the latent failure times follow a generalized family of distributions, inference for unknown parameters is provided using classical and Bayesian approaches. Particularly existence-uniqueness properties of maximum likelihood estimators are established. Subsequently interval estimators are constructed based on observed Fisher information matrix. Bayes estimates and associated highest posterior density intervals are developed using gamma-beta prior distributions by considering squared error loss function. We also study estimation problem when parameters are order restricted. The performance of all estimators is evaluated based on an extensive simulation study and comments are obtained. A real data set is also analyzed for illustration purposes.
      PubDate: 2024-05-01
       
  • Analysis of the Mt/M/1 Queueing System with Impatient Customers and Single
           Vacation

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      Abstract: Abstract We consider an Mt/M/1 queueing system with impatient customers and a single vacation, assuming the customers’ impatience is due to the server’s vacation. In the context of non-stationary sinusoidal modeling, this paper introduces systems with exponential service times and periodic (sinusoidal) Poisson arrival processes. We studied a novel analysis of an Mt/M/1 model including simultaneous vacations and impatient customers alongside the relative amplitude changes. In addition, the pointwise stationary approximation has been computed by integrating over time the formula for the stationary performance measure with the arrival rate that applies at each point in time. The time-dependent probability generating functions and the corresponding steady-state results have been obtained explicitly. We focus on five performance measures: the expected number of customers waiting in the queue during vacation, the expected customer waiting time in the queue during vacation, the probability of the server being busy, the probability of the server being on vacation and the probability of customers’ impatience. Finally, to evaluate the performance measure of queue length, we have conducted a sensitivity analysis by running a simulation for a specific set of parameters.
      PubDate: 2024-04-27
       
  • Sampling from a Neural Network

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      Abstract: Abstract In this article, the video game Dota 2 is used as an illustration of video games where two teams have to confront. This is a very popular game where billions of matches are available for enhancing statistical analysis and fostering further method developments. Here, we focus on sampling teams or pairs of teams favouring more imbalanced matches, based upon the scores observed either for one team or for a couple of teams. An artificial neural network models the expected outcome which is then used to sample teams through a Metropolis-Hastings algorithm. The main result is establishing the polynomial convergence speed bound for both cases, that is sampling random teams and sampling random pairs of teams. An empirical experiment is also provided when sampling pairs of teams for Dota after learning matches outcomes from a database of 2 million matches, showing that the convergence may happen much more quickly.
      PubDate: 2024-04-23
       
  • Analysis of Two - Part Random Effects Model for Semi-Ordinal Longitudinal
           Response

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      Abstract: Abstract We have proposed a new variable called semi-ordinal variable. This variable exhibits a combination of responses, with a portion of them taking on ordinal values and the remaining values following a continuous distribution, often with truncation. In longitudinal analyses, variable of this type may be described by a pair of regression models, for example, one approach to analyze this variable is to use ordinal regression for the ordinal component and a conditional linear model for the continuous component. We have proposed a two - part ranom effects model for longitudinal semi-ordinal responses. A full likelihood-based approach that allows yielding maximum likelihood estimates of the model parameters is used. To illustrate the utility of the proposed model, we apply a new method for analysis outlier data. Also, the model is applied to using data from a large data set excerpted from the British Household Panel Survey (BHPS) is analyzed.
      PubDate: 2024-04-19
       
  • Optimal Random Non Response Frameworks for Mean Estimation on Current
           Occasion

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      Abstract: Abstract In this paper, we propose various sampling strategies under random non response framework and proposed estimators to estimate population mean on current occasion. The formulation of the estimator is allied with Cochran (1977) and Searls (J. Am. Stat. Assoc. 59, 1225–1226 1964) in the framework of random non response. The characteristics of each proposed estimator have been studied under optimum replacement policy. We have examined the performance of these estimators under the analytical study and validated it through numerical study. We have also gauged the loss with the available complete response case and reported in numerical illustration. Suitable recommendations have been put forward to the survey statisticians for its practical application.
      PubDate: 2024-04-16
       
  • Mean and Variance for Count Regression Models Based on Reparameterized
           Distributions

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      Abstract: Abstract We introduce a new regression model for count data where the response variable is mainly in the class of inflated-parameter generalized power series (IGPS) distributions, which take automatically into account both dispersion and zero inflation phenomena. An original parameterization of these distributions is used, which is indexed by the mean and variance parameters, and not generally connected between them. An advantage of our approach is the straightforward interpretation of the regression coefficients in terms of the mean and variance comparing, for instance, to the popular generalized linear models. This attractive methodology is so simple and useful for many models. Some new mathematical and practical properties of the IGPS distributions are studied, including the quantile function, dispersion and zero-inflation indexes. Three basical IGPS models such for geometric, Bernoulli and Poisson are investigated in details. For the corresponding count regression models, the method of maximum likelihood is used for estimating the model parameters. Simulation studies are conducted to evaluate its finite sample performance. Finally, we highlight the ability of some reparameterized IGPS regression models to deal with count data which are overdispersed and zero-inflated; and then, comparing with usual models like zero inflated Poisson and negative binomial which are also reparameterized in terms of mean and variance.
      PubDate: 2024-03-14
      DOI: 10.1007/s13571-024-00325-z
       
  • Robust Statistical Modeling of Monthly Rainfall: The Minimum Density Power
           Divergence Approach

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      Abstract: Abstract Statistical modeling of monthly, seasonal, or annual rainfall data is an important research area in meteorology. These models play a crucial role in rainfed agriculture, where a proper assessment of the future availability of rainwater is necessary. The rainfall amount during a rainy month or a whole rainy season can take any positive value and some simple (one or two-parameter) probability models supported over the positive real line that are generally used for rainfall modeling are exponential, gamma, Weibull, lognormal, Pearson Type-V/VI, log-logistic, etc., where the unknown model parameters are routinely estimated using the maximum likelihood estimator (MLE). However, the presence of outliers or extreme observations is a common issue in rainfall data and the MLEs being highly sensitive to them often leads to spurious inference. Here, we discuss a robust parameter estimation approach based on the minimum density power divergence estimator (MDPDE). We fit the above four parametric models to the detrended areally-weighted monthly rainfall data from the 36 meteorological subdivisions of India for the years 1951-2014 and compare the fits based on MLE and the proposed ‘optimum’ MDPDE; the superior performance of MDPDE is showcased for several cases. For all month-subdivision combinations, we discuss the best-fit models and median rainfall amounts.
      PubDate: 2024-03-02
      DOI: 10.1007/s13571-024-00324-0
       
  • Algorithm for Detection of Illegal Discounting in North Carolina Education
           Lottery

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      Abstract: Abstract The lottery is a very lucrative industry. Popular fascination often focuses on the largest prizes. However, less attention has been paid to detecting unusual lottery buying behaviors at lower stakes. Our paper introduces a new model to detect illegal discounting in the North Carolina Education Lottery using statistical analysis of net gains and ticket buying habits. Nine outlying players are flagged and are further examined using a proposed stochastic model to calculate the range of their possible losses in the lottery. The unusual buying patterns of the players flagged as outliers are further confirmed using a K-means clustering analysis of lottery store visiting behaviors.
      PubDate: 2024-02-29
      DOI: 10.1007/s13571-024-00323-1
       
  • Rough Volatility: Fact or Artefact'

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      Abstract: Abstract We investigate the statistical evidence for the use of ‘rough’ fractional processes with Hurst exponent \(H< 0.5\) for modeling the volatility of financial assets, using a model-free approach. We introduce a non-parametric method for estimating the roughness of a function based on discrete sample, using the concept of normalized p-th variation along a sequence of partitions. Detailed numerical experiments based on sample paths of fractional Brownian motion and other fractional processes reveal good finite sample performance of our estimator for measuring the roughness of sample paths of stochastic processes. We then apply this method to estimate the roughness of realized volatility signals based on high-frequency observations. Detailed numerical experiments based on stochastic volatility models show that, even when the instantaneous volatility has diffusive dynamics with the same roughness as Brownian motion, the realized volatility exhibits rough behaviour corresponding to a Hurst exponent significantly smaller than 0.5. Comparison of roughness estimates for realized and instantaneous volatility in fractional volatility models with different values of Hurst exponent shows that, irrespective of the roughness of the spot volatility process, realized volatility always exhibits ‘rough’ behaviour with an apparent Hurst index \(\widehat{H}<0.5\) . These results suggest that the origin of the roughness observed in realized volatility time series lies in the estimation error rather than the volatility process itself.
      PubDate: 2024-02-21
      DOI: 10.1007/s13571-024-00322-2
       
  • Analysis of One-Way ANOVA Model using Synthetic Data

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      Abstract: Abstract In this paper we consider the age-old ANOVA problem of testing the equality of means of several univariate normal populations with a common unknown variance, except that the data used for analysis arise from a synthetic version of the original observations. We address two versions of the synthetic data: one obtained under Plug-In sampling(PIS) method and the other under Posterior Predictive Sampling(PPS) method. We study its distributional properties (null and non-null) and provide enough computational details. A comparison of power is also provided. As expected, the power under the PIS method is more than that under the PPS method. A measure of privacy protection is also evaluated and it turns out that the PIS method provides less protection than the PPS method, thus confirming the standard belief that accuracy of inference and privacy protection work in opposite directions. Robustness of the proposed tests under deviations from normality is also studied.
      PubDate: 2024-01-06
      DOI: 10.1007/s13571-023-00318-4
       
  • Geometric Mean Type of Proportional Reduction in Variation Measure for
           Two-Way Contingency Tables

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      Abstract: Abstract Traditional analysis of two-way contingency tables with explanatory and response variables focuses on the independence of two variables. However, if the variables do not show independence or a clear relationship, the analysis shifts to the degree of association. Various measures have been proposed to calculate the degree of association. One is the proportional reduction in variation (PRV) measure. This measure describes the PRV from the marginal distribution to the conditional distribution of the response variable. Although conventional PRV measures can assess the association of the entire contingency table, they cannot accurately assess the association for each explanatory variable. In this paper, we propose a geometric mean type of PRV (geoPRV) measure, which aims to sensitively capture the association of each explanatory variable to the response variable. Our approach uses a geometric mean, and enabling analysis without underestimating the values when the cells in the contingency table are partially biased. The geoPRV measure can be constructed using any function that satisfies specific conditions. This approach has practical advantages, and in special cases, conventional PRV measures can be expressed as geometric mean types.
      PubDate: 2024-01-03
      DOI: 10.1007/s13571-023-00320-w
       
  • Diagnostic Test for Realized Missingness in Mixed-type Data

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      Abstract: Abstract A frequent concern in analyzing incomplete multivariate measurements in mixed categorical and quantitative scales is whether missing completely at random (MCAR) is an appropriate model. Realized MCAR refers to constancy of conditional probability at realized missing data patterns and differs from always MCAR. We develop a scalable approach for diagnostics of realized MCAR in mixed-type data for which existing methods are lacking. We interestingly establish that the null framework may hold under the broader condition of observed at random (OAR) under component independence and the method cannot detect departure in the direction of OAR under independence but may do so under dependence. We demonstrate that the proposed method is easy to implement and scalable. In the special case of non-mixed type data, we face computational difficulties with existing methods whereas the proposed approach performs superiorly. The proposed approach is applied to analyze incomplete mixed-type data from the ARCAD metastatic colorectal cancer database.
      PubDate: 2023-12-20
      DOI: 10.1007/s13571-023-00317-5
       
  • Local Influence in Regression Models with Measurement Errors and Censored
           Data Considering the Student–t Distribution

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      Abstract: Abstract In this paper, the local influence approach is studied in regression models with measurement errors for multivariate censored responses under the Student-t distribution. The multivariate Student–t distribution and the multivariate normal, distributions of the independent normal class, are studied and used to compare various measuring instruments. The ECM algorithm is used to obtain maximum likelihood estimates of the model parameters and using the log-likelihood function of the complete data we obtain measures of local influence based on the methodology proposed by Zhu and Lee (Journal of the Royal Statistical Society, Series B 63:121–126, 2001) and Lee and Xu (Computational Statistics and Data Analysis 45:321–341, 2004). Finally, the described methodologies are used in real data analysis that illustrates the usefulness of the approach.
      PubDate: 2023-12-19
      DOI: 10.1007/s13571-023-00316-6
       
  • Doubly Weighted Estimation Approach for Linear Regression Analysis with
           Two-stage Cluster Samples

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      Abstract: Abstract In a two stage clusters sampling (TSCS) setup, a sample of clusters is chosen at the first stage from a large number of clusters belonging to a finite population (FP), and in the second stage a random sample of individuals is chosen from the selected cluster. In this sampling setup, it is of interest to collect responses along with certain multi-dimensional fixed covariates from all individuals selected in the second stage cluster, and examine the effects of such covariates on the responses. In some studies, the fixed covariates from the so-called sampling frame consisting of all first-stage clustered individuals may be available. Because the responses in a given cluster share a common random cluster effect, they are correlated. Thus, if the first-stage clusters based data were all available, one could estimate the regression parameters/effects by using the standard infinite population based generalized least square (GLS) approach that produces efficient estimates as compared to the simpler OLS (ordinary least square) estimates. But, in the present TSCS setup, the first-stage clustered data are not available, and hence the estimation has to be done using second-stage clusters, where the responses may not be assumed any more arising from the infinite population, rather there is a sampling effect to consider in order to develop appropriate estimating equations for the regression parameters. However, the existing four decades long studies including a pioneer work by Prasad and Rao (J. Am. Stat. Assoc., 85, 163–171 1990) used the same GLS estimation by treating the second stage clusters as the first stage clusters following a super-population model based correlation structure. In this paper, we revisit this important inference issue and find that because the existing second-stage clusters based GLS approach is constructed ignoring the sampling effect (of the first stage clusters), leave alone the efficiency gain, this approach produces biased and hence inconsistent estimates for the regression parameters and other related subsequent effects. As a remedy, on top of sampling weights we introduce an inverse correlation weight to the second stage clustered elements and provide a doubly weighted GLS (DWGLS) estimation approach which produces unbiased and consistent estimates of the regression parameters. The correlation parameters are also consistently estimated. A numerical illustration using a hypothetical two-stage cluster sample is provided to understand the estimation biases caused by sampling mis-specification under a simpler specialized linear cluster model with no covariates without any loss of generality. For the general regression case, the unbiasedness and consistency properties of the proposed estimator of the regression parameter, which is of main interest, are studied analytically in details. The asymptotic normality of the regression estimator is also studied for the construction of confidence intervals when needed.
      PubDate: 2023-12-15
      DOI: 10.1007/s13571-023-00321-9
       
  • Some Results on Estimating a Wilcoxon–Mann–Whitney Measure of Effect
           Size When There are two Covariates

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      Abstract: Abstract A basic method for characterizing the difference between two independent groups is \(\pi \) , the probability that a randomly sampled value from the first group is less than a randomly sampled value from the second group. Recently, a method for making inferences about \(\pi \) was proposed that deals with a covariate. A goal here is to report simulation results when there are two covariates. Included is a suggestion for picking the covariate points. The method is illustrated with data dealing with depressive symptoms among older adults.
      PubDate: 2023-12-06
      DOI: 10.1007/s13571-023-00319-3
       
  • Optimum Plans for Progressive Censored Competing Risk Data Under Kies
           Distribution

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      Abstract: Abstract This paper considers optimal inference for the competing risks model when the latent failure times follow the two-parameter Kies distribution with a common shape parameter. We obtain different optimum schemes for competing risks model under progressive type-II censoring scheme. The existence and uniqueness properties of maximum likelihood estimates of parameters are derived. Further observed and expected Fisher information matrices are evaluated. In sequel approximate intervals of Kies parameters are computed. A simulation study has been used to evaluate proposed estimators. Analysis of a real data set is presented as well, for illustration purpose. Furthermore, we obtain optimal censoring plans by minimizing the experimental cost and variance associated with the estimators by considering single as well as multi-objective frameworks.
      PubDate: 2023-10-21
      DOI: 10.1007/s13571-023-00315-7
       
 
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  Subjects -> MATHEMATICS (Total: 1013 journals)
    - APPLIED MATHEMATICS (92 journals)
    - GEOMETRY AND TOPOLOGY (23 journals)
    - MATHEMATICS (714 journals)
    - MATHEMATICS (GENERAL) (45 journals)
    - NUMERICAL ANALYSIS (26 journals)
    - PROBABILITIES AND MATH STATISTICS (113 journals)

PROBABILITIES AND MATH STATISTICS (113 journals)                     

Showing 1 - 98 of 98 Journals sorted alphabetically
Advances in Statistics     Open Access   (Followers: 10)
Afrika Statistika     Open Access   (Followers: 1)
American Journal of Applied Mathematics and Statistics     Open Access   (Followers: 13)
American Journal of Mathematics and Statistics     Open Access   (Followers: 9)
Annals of Data Science     Hybrid Journal   (Followers: 15)
Annual Review of Statistics and Its Application     Full-text available via subscription   (Followers: 11)
Applied Medical Informatics     Open Access   (Followers: 12)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Asian Journal of Probability and Statistics     Open Access  
Austrian Journal of Statistics     Open Access   (Followers: 4)
Biostatistics & Epidemiology     Hybrid Journal   (Followers: 6)
Cadernos do IME : Série Estatística     Open Access  
Calcutta Statistical Association Bulletin     Hybrid Journal  
Communications in Mathematics and Statistics     Hybrid Journal   (Followers: 3)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics: Case Studies, Data Analysis and Applications     Hybrid Journal  
Comunicaciones en Estadística     Open Access  
Econometrics and Statistics     Hybrid Journal   (Followers: 2)
Forecasting     Open Access   (Followers: 1)
Foundations and Trends® in Optimization     Full-text available via subscription   (Followers: 2)
Frontiers in Applied Mathematics and Statistics     Open Access   (Followers: 2)
Game Theory     Open Access   (Followers: 2)
Geoinformatics & Geostatistics     Hybrid Journal   (Followers: 10)
Geomatics, Natural Hazards and Risk     Open Access   (Followers: 14)
Indonesian Journal of Applied Statistics     Open Access  
International Game Theory Review     Hybrid Journal  
International Journal of Advanced Statistics and IT&C for Economics and Life Sciences     Open Access  
International Journal of Advanced Statistics and Probability     Open Access   (Followers: 7)
International Journal of Algebra and Statistics     Open Access   (Followers: 4)
International Journal of Applied Mathematics and Statistics     Full-text available via subscription   (Followers: 4)
International Journal of Ecological Economics and Statistics     Full-text available via subscription   (Followers: 4)
International Journal of Energy and Statistics     Hybrid Journal   (Followers: 4)
International Journal of Game Theory     Hybrid Journal   (Followers: 3)
International Journal of Mathematics and Statistics     Full-text available via subscription   (Followers: 2)
International Journal of Multivariate Data Analysis     Hybrid Journal  
International Journal of Probability and Statistics     Open Access   (Followers: 3)
International Journal of Statistics & Economics     Full-text available via subscription   (Followers: 6)
International Journal of Statistics and Applications     Open Access   (Followers: 2)
International Journal of Statistics and Probability     Open Access   (Followers: 3)
International Journal of Statistics in Medical Research     Hybrid Journal   (Followers: 2)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Iraqi Journal of Statistical Sciences     Open Access  
Japanese Journal of Statistics and Data Science     Hybrid Journal  
Journal of Biometrics & Biostatistics     Open Access   (Followers: 4)
Journal of Cost Analysis and Parametrics     Hybrid Journal   (Followers: 5)
Journal of Environmental Statistics     Open Access   (Followers: 4)
Journal of Game Theory     Open Access   (Followers: 1)
Journal of Mathematical Economics and Finance     Full-text available via subscription  
Journal of Mathematics and Statistics Studies     Open Access  
Journal of Modern Applied Statistical Methods     Open Access   (Followers: 1)
Journal of Official Statistics     Open Access   (Followers: 2)
Journal of Quantitative Economics     Hybrid Journal  
Journal of Social and Economic Statistics     Open Access   (Followers: 4)
Journal of Statistical Theory and Practice     Hybrid Journal   (Followers: 2)
Journal of Statistics and Data Science Education     Open Access   (Followers: 2)
Journal of Survey Statistics and Methodology     Hybrid Journal   (Followers: 6)
Journal of the Indian Society for Probability and Statistics     Full-text available via subscription  
Jurnal Biometrika dan Kependudukan     Open Access   (Followers: 1)
Jurnal Ekonomi Kuantitatif Terapan     Open Access  
Jurnal Sains Matematika dan Statistika     Open Access  
Lietuvos Statistikos Darbai     Open Access   (Followers: 1)
Mathematics and Statistics     Open Access   (Followers: 2)
Methods, Data, Analyses     Open Access   (Followers: 1)
METRON     Hybrid Journal   (Followers: 2)
Nepalese Journal of Statistics     Open Access   (Followers: 1)
North American Actuarial Journal     Hybrid Journal   (Followers: 2)
Open Journal of Statistics     Open Access   (Followers: 3)
Open Mathematics, Statistics and Probability Journal     Open Access  
Pakistan Journal of Statistics and Operation Research     Open Access   (Followers: 1)
Physica A: Statistical Mechanics and its Applications     Hybrid Journal   (Followers: 7)
Probability, Uncertainty and Quantitative Risk     Open Access   (Followers: 2)
Ratio Mathematica     Open Access  
Research & Reviews : Journal of Statistics     Open Access   (Followers: 4)
Revista Brasileira de Biometria     Open Access  
Revista Colombiana de Estadística     Open Access  
RMS : Research in Mathematics & Statistics     Open Access   (Followers: 1)
Romanian Statistical Review     Open Access  
Sankhya B - Applied and Interdisciplinary Statistics     Hybrid Journal  
SIAM Journal on Mathematics of Data Science     Hybrid Journal   (Followers: 6)
SIAM/ASA Journal on Uncertainty Quantification     Hybrid Journal   (Followers: 3)
Spatial Statistics     Hybrid Journal   (Followers: 2)
Sri Lankan Journal of Applied Statistics     Open Access  
Stat     Hybrid Journal   (Followers: 1)
Stata Journal     Full-text available via subscription   (Followers: 9)
Statistica     Open Access   (Followers: 6)
Statistical Analysis and Data Mining     Hybrid Journal   (Followers: 23)
Statistical Theory and Related Fields     Hybrid Journal  
Statistics and Public Policy     Open Access   (Followers: 3)
Statistics in Transition New Series : An International Journal of the Polish Statistical Association     Open Access  
Statistics Research Letters     Open Access   (Followers: 1)
Statistics, Optimization & Information Computing     Open Access   (Followers: 5)
Stats     Open Access  
Synthesis Lectures on Mathematics and Statistics     Full-text available via subscription   (Followers: 1)
Theory of Probability and its Applications     Hybrid Journal   (Followers: 2)
Theory of Probability and Mathematical Statistics     Full-text available via subscription   (Followers: 2)
Turkish Journal of Forecasting     Open Access   (Followers: 1)
VARIANSI : Journal of Statistics and Its application on Teaching and Research     Open Access   (Followers: 4)
Zeitschrift für die gesamte Versicherungswissenschaft     Hybrid Journal  

           

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