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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted by number of followers
Statistics in Medicine     Hybrid Journal   (Followers: 149)
Journal of Econometrics     Hybrid Journal   (Followers: 85)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 78, SJR: 3.746, CiteScore: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 53)
Biometrics     Hybrid Journal   (Followers: 51)
Sociological Methods & Research     Hybrid Journal   (Followers: 49)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 43)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 42, SJR: 3.664, CiteScore: 2)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 39)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 37)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 35)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 35)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 31)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 28)
The American Statistician     Full-text available via subscription   (Followers: 27)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 25)
Journal of Applied Statistics     Hybrid Journal   (Followers: 22)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Forecasting     Hybrid Journal   (Followers: 21)
Statistical Modelling     Hybrid Journal   (Followers: 19)
Journal of Statistical Software     Open Access   (Followers: 19, SJR: 13.802, CiteScore: 16)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 18)
Computational Statistics     Hybrid Journal   (Followers: 17)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Risk Management     Hybrid Journal   (Followers: 16)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 15)
Demographic Research     Open Access   (Followers: 15)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 12)
International Statistical Review     Hybrid Journal   (Followers: 12)
Journal of Statistical Physics     Hybrid Journal   (Followers: 12)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 12)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 10)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 10)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Stata Journal     Full-text available via subscription   (Followers: 10)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 9)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Handbook of Statistics     Full-text available via subscription   (Followers: 9)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 9)
Current Research in Biostatistics     Open Access   (Followers: 9)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 8)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 8)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Global Optimization     Hybrid Journal   (Followers: 7)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Biometrical Journal     Hybrid Journal   (Followers: 6)
Significance     Hybrid Journal   (Followers: 6)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Applied Categorical Structures     Hybrid Journal   (Followers: 5)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Lifetime Data Analysis     Hybrid Journal   (Followers: 5)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
Statistical Methods and Applications     Hybrid Journal   (Followers: 5)
CHANCE     Hybrid Journal   (Followers: 5)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Metrika     Hybrid Journal   (Followers: 4)
Statistical Papers     Hybrid Journal   (Followers: 4)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 4)
TEST     Hybrid Journal   (Followers: 3)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 3)
Sankhya A     Hybrid Journal   (Followers: 3)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
Extremes     Hybrid Journal   (Followers: 2)
Optimization Letters     Hybrid Journal   (Followers: 2)
Stochastic Models     Hybrid Journal   (Followers: 2)
Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports     Hybrid Journal   (Followers: 2)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
Building Simulation     Hybrid Journal   (Followers: 2)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Sequential Analysis: Design Methods and Applications     Hybrid Journal   (Followers: 1)
Journal of the Korean Statistical Society     Hybrid Journal   (Followers: 1)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)
Statistics and Economics     Open Access  
Review of Socionetwork Strategies     Hybrid Journal  
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  

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Journal Cover
Journal of the Korean Statistical Society
Journal Prestige (SJR): 0.545
Citation Impact (citeScore): 1
Number of Followers: 1  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1226-3192 - ISSN (Online) 2005-2863
Published by Elsevier Homepage  [2974 journals]
  • Scale invariant and efficient estimation for groupwise scaled envelope
           model

    • Free pre-print version: Loading...

      Abstract: Abstract Motivated by different groups containing different group information under the heteroscedastic error structure, we propose the groupwise scaled envelope model that is invariable to scale changes and is permissible for distinct regression coefficients and the heteroscedastic error structure across groups. It retains the potential of the scaled envelope methods to keep the scale invariant and allows for both different regression coefficients and different error structures for diverse groups. Further, we demonstrate the maximum likelihood estimators and its theoretical properties including parameter identifiability, asymptotic distribution and consistency of the groupwise scaled envelope estimator. Lastly, simulation studies and a real-data example demonstrate the advantages of the groupwise scaled envelope estimators, including a comparison with the standard model estimators, groupwise envelope estimators, scaled envelope estimators and separate scaled envelope estimators.
      PubDate: 2024-07-14
       
  • Statistical inference of pth-order generalized binomial autoregressive
           model

    • Free pre-print version: Loading...

      Abstract: Abstract To capture the higher-order autocorrelation structure for finite-range integer-valued time series of counts, and to consider the interdependence between individuals, a pth-order generalized binomial autoregressive (GBAR(p)) process is proposed in this paper. The stationarity and ergodicity of the GBAR(p) model are proved, and the basic probabilistic and statistical properties of the model are discussed. The unknown parameters are estimated by the conditional least squares and conditional maximum likelihood methods. The performances of two kinds of estimators are studied via simulations, and the forecasting problem of this model is also considered in this paper. Finally, the model is applied to a real data set and compared with some existing models to investigate the rationality of the GBAR(p) model.
      PubDate: 2024-07-13
       
  • Strong convergence of a nonparametric relative error regression estimator
           under missing data with functional predictors

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      Abstract: Abstract In this paper, we develop a nonparametric estimator of the regression function for a functional explanatory variable and a scalar response variable that is subject to left truncation and right censoring. The estimator is constructed by minimizing the mean squared relative error, which is a robust criterion that reduces the impact of outliers relatively to the Nadaraya Watson estimator. We prove the pointwise and uniform convergence of the estimator under some regular conditions and assess its performance by a numerical study. We also investigate the robustness of the estimator using the influence function as a measure of sensitivity to outliers and apply the estimator to a real dataset.
      PubDate: 2024-07-07
       
  • Modeling and inferences for bounded multivariate time series of counts

    • Free pre-print version: Loading...

      Abstract: Abstract This paper considers modeling bounded multivariate time series of counts and the inferential procedures of this model. For modeling, we introduce a hybrid type model similar to the scheme of integer-valued autoregressive (INAR) and conditional autoregressive heteroscedastic (INARCH) models. To estimate the model parameters, we use the conditional least squares estimator (CLSE) and minimum density power divergence estimator (MDPDE). To evaluate the small sample performances of the proposed estimators, we conduct a Monte Carlo simulation study and demonstrate that the proposed methods work well. Real data analysis is also carried out using syphilis data in the U.S. for illustration.
      PubDate: 2024-06-25
       
  • Bayesian hierarchical spatial model for small-area estimation with
           non-ignorable nonresponses and its application to the NHANES dental caries
           data

    • Free pre-print version: Loading...

      Abstract: Abstract The National Health and Nutrition Examination Survey (NHANES) is a major program of the National Center for Health Statistics, designed to assess the health and nutritional status of adults and children in the United States. The analysis of NHANES dental caries data faces several challenges, including (1) the data were collected using a complex, multistage, stratified, unequal-probability sampling design; (2) the sample size of some primary sampling units (PSU), e.g., counties, is very small; (3) the measures of dental caries have complicated structure and correlation, and (4) there is a substantial percentage of nonresponses, which are expected not to be missing at random or non-ignorable. We propose a Bayesian hierarchical spatial model to address these analysis challenges. We develop a two-level Potts model that closely resembles the caries evolution process, and captures complicated spatial correlations between teeth and surfaces of the teeth. By adding Bayesian hierarchies to the Potts model, we account for the multistage survey sampling design, while also enabling information borrowing across PSUs for small-area estimation. We incorporate sampling weights by including them as a covariate in the model and adopt flexible B-splines to achieve robust inference. We account for non-ignorable missing outcomes and covariates using the selection model. We use data augmentation coupled with the noisy Monte Carlo algorithm to overcome the numerical difficulty caused by doubly-intractable normalizing constants and sample posteriors. Our analysis results show strong spatial associations between teeth and tooth surfaces, including that dental hygienic factors, such as fluorosis and sealant, reduce dental disease risks.
      PubDate: 2024-06-22
       
  • An index for measuring degree of departure from symmetry for ordinal
           square contingency tables

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      Abstract: Abstract For the analysis of square contingency tables with the same row and column ordinal classifications, this study proposes an index for measuring the degree of departure from the symmetry model using new cumulative probabilities. The proposed index is constructed based on the Cressie and Read’s power divergence, or the weighted average of the Patil and Taillie’s diversity index. This study derives a plug-in estimator of the proposed index and an approximate confidence interval for the proposed index. The estimator of the proposed index is expected to reduce the bias more than the estimator of the existing index, even when the sample size is not large. The proposed index is identical to the existing index under the conditional symmetry model. Therefore, assuming the probability structure in which the conditional symmetry model holds, the performances of plug-in estimators of the proposed and existing indexes can be simply compared. Through numerical examples and real data analysis, the usefulness of the proposed index compared to the existing index is demonstrated.
      PubDate: 2024-06-16
       
  • Optimal designs for comparing several regression curves

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      Abstract: Abstract This article is concerned with the optimal design problem of efficient statistical inference for comparing several regression curves estimated from samples of independent measurements. The objective is to find the \(\mu ^c_{p}\) -optimal designs that minimize an \(L_p\) -norm of the asymptotic variance of the prediction for the contrasts of k regression curves. General equivalence theorems are established to verify the \(\mu ^c_p\) -optimality in the set of all approximate designs. Invariant property with respect to model reparameterization are also obtained. The results obtained for the linear models are extended to the situation of generalized linear models. Three examples are presented to illustrate the applications of the obtained results.
      PubDate: 2024-06-14
       
  • Testing for conditional independence of survival time from covariate

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      Abstract: Abstract This study examined the test of independence of survival time from a covariate in a more general setting using empirical process techniques. Previous research has been extended in several ways: (1) allow incompleteness of observation owing to censoring (2) allow the time-dependent covariate (3) allow the non-uniform covariate (4) prove the validity of weighted bootstrap to implement the proposed testing procedure. Certain classes of test statistics that are functionals of a natural empirical process were studied, and the limiting distribution of these statistics was then derived using the functional delta method. The limiting distributions included some linear functionals of zero mean tight Brownian bridges under the null hypothesis, and the tests were consistent against general alternatives. Tests implemented using weighted bootstrap were shown to be valid. The proposals are illustrated via simulation studies and an application to acute leukemia data.
      PubDate: 2024-06-01
       
  • Sequential online monitoring for autoregressive time series of counts

    • Free pre-print version: Loading...

      Abstract: Abstract This study considers the online monitoring problem for detecting the parameter change in time series of counts. For this task, we construct a monitoring process based on the residuals obtained from integer-valued generalized autoregressive conditional heteroscedastic (INGARCH) models. We consider this problem within a more general framework using martingale difference sequences as the monitoring problem on GARCH-type processes based on the residuals or score vectors can be viewed as a special case of the monitoring problems on martingale differences. The limiting behavior of the stopping rule is investigated in this general set-up and is applied to the INGARCH processes. To assess the performance of our method, we conduct Monte Carlo simulations. A real data analysis is also provided for illustration. Our findings in this empirical study demonstrate the validity of the proposed monitoring process.
      PubDate: 2024-06-01
       
  • Use of ridge calibration method in predicting election results

    • Free pre-print version: Loading...

      Abstract: Abstract Ridge calibration is a penalized method used in survey sampling to reduce the variability of the final set of weights by relaxing the linear restrictions. We proposed a method for selecting the penalty parameter that minimizes the estimated mean squared error of the mean estimator when estimated auxiliary information is used. We showed that the proposed estimator is asymptotically equivalent to the generalized regression estimator. A simple simulation study shows that our estimator has the smaller MSE compared to the traditional calibration ones. We applied our method to predict election result using National Barometer Survey and Korea Social Integration Survey.
      PubDate: 2024-06-01
       
  • Logistic regression models for elastic shape of curves based on tangent
           representations

    • Free pre-print version: Loading...

      Abstract: Abstract Shape analysis is widely used in many application areas such as computer vision, medical and biological studies. One challenge to analyze the shape of an object in an image is its invariant property to shape-preserving transformations. To measure the distance or dissimilarity between two different shapes, we worked with the square-root velocity function (SRVF) representation and the elastic metric. Since shapes are inherently high-dimensional in a nonlinear space, we adopted a tangent space at the mean shape and a few principal components (PCs) on the linearized space. We proposed classification methods based on logistic regression using these PCs and tangent vectors with the elastic net penalty. We then compared its performance with other model-based methods for shape classification in application to shape of algae in watersheds as well as simulated data generated by the mixture of von Mises-Fisher distributions.
      PubDate: 2024-06-01
       
  • A self-normalization test for structural breaks in a regression model for
           panel data sets

    • Free pre-print version: Loading...

      Abstract: Abstract We construct a new structural break test in a panel regression model using the self-normalization method. The self-normalization test is shown to be superior to an existing test in that the former is theoretically and experimentally valid for regression models with serially and/or cross-sectionally correlated errors while the latter is not. We derive the asymptotic null distribution of the self-normalization test and its consistency under an alternative hypothesis. Unlike the existing test requiring bootstrap computation for critical values, the self-normalization test is implemented easily with a set of simple critical values. A Monte Carlo experiment reports that the self-normalization resolves the severe over-size problem of the existing test under serial and/or cross-sectional error correlation.
      PubDate: 2024-06-01
       
  • Disseminating massive frequency tables by masking aggregated cell
           frequencies

    • Free pre-print version: Loading...

      Abstract: Abstract We propose a confidential approach for disseminating frequency tables constructed for any combination of key variables in the given microdata, including those of hierarchical key variables. The system generates all possible frequency tables by either marginalizing or aggregating fully joint frequency tables of key variables while protecting the original cells with low frequencies through two masking steps: the small cell adjustments for joint tables followed by the proposed algorithm called information loss bounded aggregation for aggregated cells. The two-step approach is designed to control both disclosure risk and information loss by ensuring the k-anonymity of original cells with small frequencies while keeping the loss within a bounded limit.
      PubDate: 2024-06-01
       
  • Asymptotic of the number of false change points of the fused lasso signal
           approximator

    • Free pre-print version: Loading...

      Abstract: Abstract It is well-known that the fused lasso signal approximator (FLSA) is inconsistent in change point detection under the presence of staircase blocks in true mean values. The existing studies focus on modifying the FLSA model to remedy this inconsistency. However, the inconsistency of the FLSA does not severely degrade the performance in change point detection if the FLSA can identify all true change points and the estimated change points set is sufficiently close to the true change points set. In this study, we investigate some asymptotic properties of the FLSA under the assumption of the noise level \(\sigma _n = o(n \log n)\) . To be specific, we show that all the falsely segmented blocks are sub-blocks of true staircase blocks if the noise level is sufficiently low and a tuning parameter is chosen appropriately. In addition, each false change point of the optimal FLSA estimate can be associated with a vertex of a concave majorant or a convex minorant of a discrete Brownian bridge. Based on these results, we derive an asymptotic distribution of the number of false change points and provide numerical examples supporting the theoretical results.
      PubDate: 2024-06-01
       
  • Gradient-based kernel variable selection for support vector hazards
           machine

    • Free pre-print version: Loading...

      Abstract: Abstract This study aims to improve the predictive performance for the event time through the machine learning model and find informative variables in the time-to-event data, simultaneously. To address this issue, after regarding the time-to-event data as the dichotomized counting processes data for predicting survival time, we consider the time-dependent support vector machine (SVM) framework for the dichotomized counting process data, where the decision function in this framework consists of the time-independent risk score and time-dependent intercept. Also, we consider the empirical partial derivative of the risk score function with respect to each marginal predictor as the indicator for the important predictor. Through this approach, it is possible to predict survival time and find variables that affect on the survival time at the same time. Simulation studies were conducted to confirm the performance of the model, and real data analysis was conducted by predicting the survival time of the lung cancer after the diagnosis and selecting genes associate with lung cancer through human gene data.
      PubDate: 2024-06-01
       
  • Byzantine-resilient decentralized network learning

    • Free pre-print version: Loading...

      Abstract: Abstract Decentralized federated learning based on fully normal nodes has drawn attention in modern statistical learning. However, due to data corruption, device malfunctioning, malicious attacks and some other unexpected behaviors, not all nodes can obey the estimation process and the existing decentralized federated learning methods may fail. An unknown number of abnormal nodes, called Byzantine nodes, arbitrarily deviate from their intended behaviors, send wrong messages to their neighbors and affect all honest nodes across the entire network through passing polluted messages. In this paper, we focus on decentralized federated learning in the presence of Byzantine attacks and then propose a unified Byzantine-resilient framework based on the network gradient descent and several robust aggregation rules. Theoretically, the convergence of the proposed algorithm is guaranteed under some weakly balanced conditions of network structure. The finite-sample performance is studied through simulations under different network topologies and various Byzantine attacks. An application to Communities and Crime Data is also presented.
      PubDate: 2024-06-01
       
  • Large sample properties of maximum likelihood estimator using moving
           extremes ranked set sampling

    • Free pre-print version: Loading...

      Abstract: Abstract In this paper, we investigate the maximum likelihood estimator (MLE) for the parameter \(\theta\) in the probability density function \(f(x;\theta )\) . We specifically focus on the application of moving extremes ranked set sampling (MERSS) and analyze its properties in large samples. We establish the existence and uniqueness of the MLE for two common distributions when utilizing MERSS. Our theoretical analysis demonstrates that the MLE obtained through MERSS is, at the very least, as efficient as the MLE obtained through simple random sampling with an equivalent sample size. To substantiate these theoretical findings, we conduct numerical experiments. Furthermore, we explore the implications of imperfect ranking and provide a practical illustration by applying our approach to a real dataset.
      PubDate: 2024-06-01
       
  • Multiple values-inflated bivariate INAR time series of counts: featuring
           zero–one inflated Poisson-Lindly case

    • Free pre-print version: Loading...

      Abstract: Abstract This study considers multiple values-inflated bivariate integer-valued autoregressive (MV-inflated BINAR) models. It develops the inferential procedures for parameter estimation on this model, which apply to constructing a change point test and outlier detection rule. We first introduce the MV-inflated BINAR model with one parameter exponential family and Poisson-Lindley innovations. Then, we propose a quasi-maximum likelihood estimator (QMLE) and divergence-based estimator featuring minimum density power divergence estimator (MDPDE) for robust estimation. To evaluate the performance of these estimators, we conduct Monte Carlo simulations and demonstrate the adequacy of MDPDE in zero–one inflated models. Real data analysis is also carried out using the number of monthly earthquake cases in the United States.
      PubDate: 2024-06-01
       
  • Correction: Disseminating massive frequency tables by masking aggregated
           cell frequencies

    • Free pre-print version: Loading...

      PubDate: 2024-04-03
       
  • Variants of non-symmetric correspondence analysis for nominal and ordinal
           variables

    • Free pre-print version: Loading...

      Abstract: Abstract Non-symmetric correspondence analysis (NSCA) is a multivariate data analysis technique that has gained increasing attention in recent years. NSCA is an extension of traditional correspondence analysis that allows for the analysis of asymmetric association between two or more categorical variables. NSCA involves graphically depicting the one-way relationship between variables cross classified in a contingency table through a biplot. This paper provides a comprehensive overview of the popular approaches of NSCA developed over the years. Some fundamental variations in the family of NSCA such as Simple NSCA, Doubly Ordered NSCA, Singly Ordered NSCA, Three-way Nominal NSCA, Triply Ordered NSCA etc. are discussed thoroughly. A systematic step-by-step algorithms for each variant of NSCA and their demonstrations are neatly presented. Further a summary of NSCA variants in literature, the concise tabular presentation of R-packages developed for variants of CA/NSCA and a collection of variety of datasets where NSCA is performed are the key features of the paper. Moreover, we compare and contrast the method of NSCA with multinomial logistic regression (MNLR) to discuss some disparities between both the approaches. The paper aims to provide the theoretical, practical and computational issues of NSCA in structured manner and to highlight the further challenges with reference to NSCA.
      PubDate: 2024-03-23
       
 
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              [Sort alphabetically]   [Restore default list]

  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted by number of followers
Statistics in Medicine     Hybrid Journal   (Followers: 149)
Journal of Econometrics     Hybrid Journal   (Followers: 85)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 78, SJR: 3.746, CiteScore: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 53)
Biometrics     Hybrid Journal   (Followers: 51)
Sociological Methods & Research     Hybrid Journal   (Followers: 49)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 43)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 42, SJR: 3.664, CiteScore: 2)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 39)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 37)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 35)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 35)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 31)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 28)
The American Statistician     Full-text available via subscription   (Followers: 27)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 25)
Journal of Applied Statistics     Hybrid Journal   (Followers: 22)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Forecasting     Hybrid Journal   (Followers: 21)
Statistical Modelling     Hybrid Journal   (Followers: 19)
Journal of Statistical Software     Open Access   (Followers: 19, SJR: 13.802, CiteScore: 16)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 18)
Computational Statistics     Hybrid Journal   (Followers: 17)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Risk Management     Hybrid Journal   (Followers: 16)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 15)
Demographic Research     Open Access   (Followers: 15)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 12)
International Statistical Review     Hybrid Journal   (Followers: 12)
Journal of Statistical Physics     Hybrid Journal   (Followers: 12)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 12)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 10)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 10)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Stata Journal     Full-text available via subscription   (Followers: 10)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 9)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Handbook of Statistics     Full-text available via subscription   (Followers: 9)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 9)
Current Research in Biostatistics     Open Access   (Followers: 9)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 8)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 8)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Global Optimization     Hybrid Journal   (Followers: 7)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Biometrical Journal     Hybrid Journal   (Followers: 6)
Significance     Hybrid Journal   (Followers: 6)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Applied Categorical Structures     Hybrid Journal   (Followers: 5)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Lifetime Data Analysis     Hybrid Journal   (Followers: 5)
Optimization Methods and Software     Hybrid Journal   (Followers: 5)
Statistical Methods and Applications     Hybrid Journal   (Followers: 5)
CHANCE     Hybrid Journal   (Followers: 5)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Metrika     Hybrid Journal   (Followers: 4)
Statistical Papers     Hybrid Journal   (Followers: 4)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 4)
TEST     Hybrid Journal   (Followers: 3)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 3)
Sankhya A     Hybrid Journal   (Followers: 3)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
Extremes     Hybrid Journal   (Followers: 2)
Optimization Letters     Hybrid Journal   (Followers: 2)
Stochastic Models     Hybrid Journal   (Followers: 2)
Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports     Hybrid Journal   (Followers: 2)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
Building Simulation     Hybrid Journal   (Followers: 2)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Sequential Analysis: Design Methods and Applications     Hybrid Journal   (Followers: 1)
Journal of the Korean Statistical Society     Hybrid Journal   (Followers: 1)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)
Statistics and Economics     Open Access  
Review of Socionetwork Strategies     Hybrid Journal  
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  

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