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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted by number of followers
Review of Economics and Statistics     Hybrid Journal   (Followers: 275)
Statistics in Medicine     Hybrid Journal   (Followers: 141)
Journal of Econometrics     Hybrid Journal   (Followers: 84)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 76, SJR: 3.746, CiteScore: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Biometrics     Hybrid Journal   (Followers: 49)
Sociological Methods & Research     Hybrid Journal   (Followers: 48)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 42)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 41, SJR: 3.664, CiteScore: 2)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 37)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 36)
Annals of Applied Statistics     Full-text available via subscription   (Followers: 35)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 35)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 34)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 30)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 28)
The American Statistician     Full-text available via subscription   (Followers: 25)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 23)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Forecasting     Hybrid Journal   (Followers: 21)
Journal of Applied Statistics     Hybrid Journal   (Followers: 20)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 19)
Statistical Modelling     Hybrid Journal   (Followers: 18)
International Journal of Quality, Statistics, and Reliability     Open Access   (Followers: 18)
Journal of Statistical Software     Open Access   (Followers: 18, SJR: 13.802, CiteScore: 16)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 17)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Computational Statistics     Hybrid Journal   (Followers: 16)
Risk Management     Hybrid Journal   (Followers: 16)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 15)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Demographic Research     Open Access   (Followers: 14)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 13)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
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: 11)
International Statistical Review     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)
Journal of Probability and Statistics     Open Access   (Followers: 10)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 9)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 9)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Stata Journal     Full-text available via subscription   (Followers: 9)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 8)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Current Research in Biostatistics     Open Access   (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 Statistical Planning and Inference     Hybrid Journal   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Biometrical Journal     Hybrid Journal   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Lifetime Data Analysis     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)
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)
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)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 3)
Sankhya A     Hybrid Journal   (Followers: 3)
Journal of Statistical and Econometric Methods     Open Access   (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)
International Journal of Stochastic Analysis     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)
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  
Journal of the Korean Statistical Society     Hybrid Journal  

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Similar Journals
Journal Cover
Computational Statistics
Journal Prestige (SJR): 0.803
Citation Impact (citeScore): 1
Number of Followers: 16  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1613-9658 - ISSN (Online) 0943-4062
Published by Springer-Verlag Homepage  [2468 journals]
  • Degree selection methods for curve estimation via Bernstein polynomials

    • Free pre-print version: Loading...

      Abstract: Abstract Bernstein Polynomial (BP) bases can uniformly approximate any continuous function based on observed noisy samples. However, a persistent challenge is the data-driven selection of a suitable degree for the BPs. In the absence of noise, asymptotic theory suggests that a larger degree leads to better approximation. However, in the presence of noise, which reduces bias, a larger degree also results in larger variances due to high-dimensional parameter estimation. Thus, a balance in the classic bias-variance trade-off is essential. The main objective of this work is to determine the minimum possible degree of the approximating BPs using probabilistic methods that are robust to various shapes of an unknown continuous function. Beyond offering theoretical guidance, the paper includes numerical illustrations to address the issue of determining a suitable degree for BPs in approximating arbitrary continuous functions.
      PubDate: 2024-03-02
       
  • Automatic piecewise linear regression

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      Abstract: Abstract Regression modelling often presents a trade-off between predictiveness and interpretability. Highly predictive and popular tree-based algorithms such as Random Forest and boosted trees predict very well the outcome of new observations, but the effect of the predictors on the result is hard to interpret. Highly interpretable algorithms like linear effect-based boosting and MARS, on the other hand, are typically less predictive. Here we propose a novel regression algorithm, automatic piecewise linear regression (APLR), that combines the predictiveness of a boosting algorithm with the interpretability of a MARS model. In addition, as a boosting algorithm, it automatically handles variable selection, and, as a MARS-based approach, it takes into account non-linear relationships and possible interaction terms. We show on simulated and real data examples how APLR’s performance is comparable to that of the top-performing approaches in terms of prediction, while offering an easy way to interpret the results. APLR has been implemented in C++ and wrapped in a Python package as a Scikit-learn compatible estimator.
      PubDate: 2024-03-01
       
  • Correction to: Sequential linear regression for conditional mean
           imputation of longitudinal continuous outcomes under reference‑based
           assumptions

    • Free pre-print version: Loading...

      PubDate: 2024-02-24
       
  • Variational Bayesian Lasso for spline regression

    • Free pre-print version: Loading...

      Abstract: Abstract This work presents a new scalable automatic Bayesian Lasso methodology with variational inference for non-parametric splines regression that can capture the non-linear relationship between a response variable and predictor variables. Note that under non-parametric point of view the regression curve is assumed to lie in a infinite dimension space. Regression splines use a finite approximation of this infinite space, representing the regression function by a linear combination of basis functions. The crucial point of the approach is determining the appropriate number of bases or equivalently number of knots, avoiding over-fitting/under-fitting. A decision-theoretic approach was devised for knot selection. Comprehensive simulation studies were conducted in challenging scenarios to compare alternative criteria for knot selection, thereby ensuring the efficacy of the proposed algorithms. Additionally, the performance of the proposed method was assessed using real-world datasets. The novel procedure demonstrated good performance in capturing the underlying data structure by selecting the appropriate number of knots/basis.
      PubDate: 2024-02-24
       
  • Generation of normal distributions revisited

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      Abstract: Abstract Normally distributed random numbers are commonly used in scientific computing in various fields. It is important to generate a set of random numbers as close to a normal distribution as possible for reducing initial fluctuations. Two types of samples from a uniform distribution are examined as source samples for inverse transform sampling methods. Three types of inverse transform sampling methods with new approximations of inverse cumulative distribution functions are also discussed for converting uniformly distributed source samples to normally distributed samples.
      PubDate: 2024-02-23
       
  • Bayesian estimation of the number of species from Poisson-Lindley
           stochastic abundance model using non-informative priors

    • Free pre-print version: Loading...

      Abstract: Abstract In this article, we propose a Poisson-Lindley distribution as a stochastic abundance model in which the sample is according to the independent Poisson process. Jeffery’s and Bernardo’s reference priors have been obtaining and proposed the Bayes estimators of the number of species for this model. The proposed Bayes estimators have been compared with the corresponding profile and conditional maximum likelihood estimators for their square root of the risks under squared error loss function (SELF). Jeffery’s and Bernardo’s reference priors have been considered and compared with the Bayesian approach based on biological data.
      PubDate: 2024-02-23
       
  • Bayesian regression models in gretl: the BayTool package

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      Abstract: Abstract This article presents the gretl package BayTool which integrates the software functionalities, mostly concerned with frequentist approaches, with Bayesian estimation methods of commonly used econometric models. Computational efficiency is achieved by pairing an extensive use of Gibbs sampling for posterior simulation with the possibility of splitting single-threaded experiments into multiple cores or machines by means of parallelization. From the user’s perspective, the package requires only basic knowledge of gretl scripting to fully access its functionality, while providing a point-and-click solution in the form of a graphical interface for a less experienced audience. These features, in particular, make BayTool stand out as an excellent teaching device without sacrificing more advanced or complex applications.
      PubDate: 2024-02-21
       
  • Bayesian sequential probability ratio test for vaccine efficacy trials

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      Abstract: Abstract Designing vaccine efficacy (VE) trials often requires recruiting large numbers of participants when the diseases of interest have a low incidence. When developing novel vaccines, such as for COVID-19 disease, the plausible range of VE is quite large at the design stage. Thus, the number of events needed to demonstrate efficacy above a pre-defined regulatory threshold can be difficult to predict and the time needed to accrue the necessary events can often be long. Therefore, it is advantageous to evaluate the efficacy at earlier interim analysis in the trial to potentially allow the trials to stop early for overwhelming VE or futility. In such cases, incorporating interim analyses through the use of the sequential probability ratio test (SPRT) can be helpful to allow for multiple analyses while controlling for both type-I and type-II errors. In this article, we propose a Bayesian SPRT for designing a vaccine trial for comparing a test vaccine with a control assuming two Poisson incidence rates. We provide guidance on how to choose the prior distribution and how to optimize the number of events for interim analyses to maximize the efficiency of the design. Through simulations, we demonstrate how the proposed Bayesian SPRT performs better when compared with the corresponding frequentist SPRT. An R repository to implement the proposed method is placed at: https://github.com/Merck/bayesiansprt.
      PubDate: 2024-02-20
       
  • Overlapping coefficient in network-based semi-supervised clustering

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      Abstract: Abstract Network-based Semi-Supervised Clustering (NeSSC) is a semi-supervised approach for clustering in the presence of an outcome variable. It uses a classification or regression model on resampled versions of the original data to produce a proximity matrix that indicates the magnitude of the similarity between pairs of observations measured with respect to the outcome. This matrix is transformed into a complex network on which a community detection algorithm is applied to search for underlying community structures which is a partition of the instances into highly homogeneous clusters to be evaluated in terms of the outcome. In this paper, we focus on the case the outcome variable to be used in NeSSC is numeric and propose an alternative selection criterion of the optimal partition based on a measure of overlapping between density curves as well as a penalization criterion which takes accounts for the number of clusters in a candidate partition. Next, we consider the performance of the proposed method for some artificial datasets and for 20 different real datasets and compare NeSSC with the other three popular methods of semi-supervised clustering with a numeric outcome. Results show that NeSSC with the overlapping criterion works particularly well when a reduced number of clusters are scattered localized.
      PubDate: 2024-02-19
       
  • First exit and Dirichlet problem for the nonisotropic tempered $$\alpha$$
           -stable processes

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      Abstract: Abstract This paper discusses the first exit and Dirichlet problems of the nonisotropic tempered \(\alpha\) -stable process \(X_t\) . The upper bounds of all moments of the first exit position \(\left X_{\tau _D}\right \) and the first exit time \(\tau _D\) are explicitly obtained. It is found that the probability density function of \(\left X_{\tau _D}\right \) or \(\tau _D\) exponentially decays with the increase of \(\left X_{\tau _D}\right \) or \(\tau _D\) , and \(\mathrm{E}\left[ \tau _D\right] \sim \mathrm{E}\left[ \left X_{\tau _D}-\mathrm{E}\left[ X_{\tau _D}\right] \right ^2\right]\) , \(\mathrm{E}\left[ \tau _D\right] \sim \left \mathrm{E}\left[ X_{\tau _D}\right] \right \) . Next, we obtain the Feynman–Kac representation of the Dirichlet problem by employing the semigroup theory. Furthermore, averaging the generated trajectories of the stochastic process leads to the solution of the Dirichlet problem, which is also verified by numerical experiments.
      PubDate: 2024-02-15
       
  • Some new invariant sum tests and MAD tests for the assessment of
           Benford’s law

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      Abstract: Abstract The Benford law is used world-wide for detecting non-conformance or data fraud of numerical data. It says that the significand of a data set from the universe is not uniformly, but logarithmically distributed. Especially, the first non-zero digit is One with an approximate probability of 0.3. There are several tests available for testing Benford, the best known are Pearson’s \(\chi ^2\) -test, the Kolmogorov–Smirnov test and a modified version of the MAD-test. In the present paper we propose some tests, three of the four invariant sum tests are new and they are motivated by the sum invariance property of the Benford law. Two distance measures are investigated, Euclidean and Mahalanobis distance of the standardized sums to the orign. We use the significands corresponding to the first significant digit as well as the second significant digit, respectively. Moreover, we suggest inproved versions of the MAD-test and obtain critical values that are independent of the sample sizes. For illustration the tests are applied to specifically selected data sets where prior knowledge is available about being or not being Benford. Furthermore we discuss the role of truncation of distributions.
      PubDate: 2024-02-13
       
  • Convergence of the CUSUM estimation for a mean shift in linear processes
           with random coefficients

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      Abstract: Abstract Let \(\{X_{i},1\le i\le n\}\) be a sequence of linear process based on dependent random variables with random coefficients, which has a mean shift at an unknown location. The cumulative sum (CUSUM, for short) estimator of the change point is studied. The strong convergence, \(L_{r}\) convergence, complete convergence and the rate of strong convergence are established for the CUSUM estimator under some mild conditions. These results improve and extend the corresponding ones in the literature. Simulation studies and two real data examples are also provided to support the theoretical results.
      PubDate: 2024-02-12
       
  • Finite mixture of regression models for censored data based on the skew-t
           distribution

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      Abstract: Abstract Finite mixture models have been widely used to model and analyze data from heterogeneous populations. In practical scenarios, these types of data often confront upper and/or lower detection limits due to the constraints imposed by experimental apparatuses. Additional complexity arises when measures of each mixture component significantly deviate from the normal distribution, manifesting characteristics such as multimodality, asymmetry, and heavy-tailed behavior, simultaneously. This paper introduces a flexible model tailored for censored data to address these intricacies, leveraging the finite mixture of skew-t distributions. An Expectation Conditional Maximization Either (ECME) algorithm, is developed to efficiently derive parameter estimates by iteratively maximizing the observed data log-likelihood function. The algorithm has closed-form expressions at the E-step that rely on formulas for the mean and variance of truncated skew-t distributions. Moreover, a method based on general information principles is presented for approximating the asymptotic covariance matrix of the estimators. Results obtained from the analysis of both simulated and real datasets demonstrate the proposed method’s effectiveness.
      PubDate: 2024-02-10
       
  • Analysis of estimating the Bayes rule for Gaussian mixture models with a
           specified missing-data mechanism

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      Abstract: Abstract Semi-supervised learning approaches have been successfully applied in a wide range of engineering and scientific fields. This paper investigates the generative model framework with a missingness mechanism for unclassified observations, as introduced by Ahfock and McLachlan (Stat Comput 30:1–12, 2020). We show that in a partially classified sample, a classifier using Bayes’ rule of allocation with a missing-data mechanism can surpass a fully supervised classifier in a two-class normal homoscedastic model, especially with moderate to low overlap and proportion of missing class labels, or with large overlap but few missing labels. It also outperforms a classifier with no missing-data mechanism regardless of the overlap region or the proportion of missing class labels. Our exploration of two- and three-component normal mixture models with unequal covariances through simulations further corroborates our findings. Finally, we illustrate the use of the proposed classifier with a missing-data mechanism on interneuronal and skin lesion datasets.
      PubDate: 2024-02-10
       
  • Fitting concentric elliptical shapes under general model

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      Abstract: Abstract Fitting concentric ellipses is a crucial yet challenging task in image processing, pattern recognition, and astronomy. To address this complexity, researchers have introduced simplified models by imposing geometric assumptions. These assumptions enable the linearization of the model through reparameterization, allowing for the extension of various fitting methods. However, these restrictive assumptions often fail to hold in real-world scenarios, limiting their practical applicability. In this work, we propose two novel estimators that relax these assumptions: the Least Squares method (LS) and the Gradient Algebraic Fit (GRAF). Since these methods are iterative, we provide numerical implementations and strategies for obtaining reliable initial guesses. Moreover, we employ perturbation theory to conduct a first-order analysis, deriving the leading terms of their Mean Squared Errors and their theoretical lower bounds. Our theoretical findings reveal that the GRAF is statistically efficient, while the LS method is not. We further validate our theoretical results and the performance of the proposed estimators through a series of numerical experiments on both real and synthetic data.
      PubDate: 2024-02-09
       
  • A simulation model to analyze the behavior of a faculty retirement plan: a
           case study in Mexico

    • Free pre-print version: Loading...

      Abstract: Abstract The main goal in this study was to determine confidence intervals for average age, average seniority, and average money-savings, for faculty members in a university retirement system using a simulation model. The simulation—built-in Arena—considers age, seniority, and the probability of continuing in the institution as the main input random variables in the model. An annual interest rate of 7% and an average annual salary increase of 3% were considered. The scenario simulated consisted of the teacher and the university making contributions, the faculty 5% of his salary, and the university 5% of the teacher’s salary. Since the base salaries with which teachers join to university are variable, we considered a monthly salary of MXN 23 181.2, corresponding to full-time teachers with middle salaries. The results obtained by a simulation of 30 replicates showed that the confidence intervals for the average age at retirement were (55.0, 55.2) years, for the average seniority (22.1, 22.3) years, and for the average savings amount (329 795.2, 341 287.0) MXN. Moreover, the risk that a retiree of 62 years of age and more of 25 years of work, is alive after his savings runs out is approximately 98% and this happens at 64 years of age.
      PubDate: 2024-02-09
       
  • Correction to: Bootstrapping binary GEV regressions for imbalanced
           datasets

    • Free pre-print version: Loading...

      PubDate: 2024-02-01
       
  • Correction to: Evaluating countries’ performances by means of rank
           trajectories: functional measures of magnitude and evolution

    • Free pre-print version: Loading...

      PubDate: 2024-02-01
       
  • High-dimensional data analysis and visualisation

    • Free pre-print version: Loading...

      PubDate: 2024-02-01
       
  • Topic based quality indexes assessment through sentiment

    • Free pre-print version: Loading...

      Abstract: Abstract This paper proposes a new methodology called TOpic modeling Based Index Assessment through Sentiment (TOBIAS). This method aims at modeling the effects of the topics, moods, and sentiments of the comments describing a phenomenon upon its overall rating. TOBIAS is built combining different techniques and methodologies. Firstly, Sentiment Analysis identifies sentiments, emotions, and moods, and Topic Modeling finds the main relevant topics inside comments. Then, Partial Least Square Path Modeling estimates how they affect an overall rating that summarizes the performance of the analyzed phenomenon. We carried out TOBIAS on a real case study on the university courses’ quality evaluated by the University of Cagliari (Italy) students. We found TOBIAS able to provide interpretable results on the impact of discussed topics by students with their expressed sentiments, emotions, and moods and with the overall rating.
      PubDate: 2024-02-01
       
 
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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
Review of Economics and Statistics     Hybrid Journal   (Followers: 275)
Statistics in Medicine     Hybrid Journal   (Followers: 141)
Journal of Econometrics     Hybrid Journal   (Followers: 84)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 76, SJR: 3.746, CiteScore: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Biometrics     Hybrid Journal   (Followers: 49)
Sociological Methods & Research     Hybrid Journal   (Followers: 48)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 42)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 41, SJR: 3.664, CiteScore: 2)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 37)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 36)
Annals of Applied Statistics     Full-text available via subscription   (Followers: 35)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 35)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 34)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 30)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 28)
The American Statistician     Full-text available via subscription   (Followers: 25)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 23)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Forecasting     Hybrid Journal   (Followers: 21)
Journal of Applied Statistics     Hybrid Journal   (Followers: 20)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 19)
Statistical Modelling     Hybrid Journal   (Followers: 18)
International Journal of Quality, Statistics, and Reliability     Open Access   (Followers: 18)
Journal of Statistical Software     Open Access   (Followers: 18, SJR: 13.802, CiteScore: 16)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 17)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Computational Statistics     Hybrid Journal   (Followers: 16)
Risk Management     Hybrid Journal   (Followers: 16)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 15)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Demographic Research     Open Access   (Followers: 14)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 13)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
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: 11)
International Statistical Review     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)
Journal of Probability and Statistics     Open Access   (Followers: 10)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 9)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 9)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Stata Journal     Full-text available via subscription   (Followers: 9)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 8)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Current Research in Biostatistics     Open Access   (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 Statistical Planning and Inference     Hybrid Journal   (Followers: 7)
Queueing Systems     Hybrid Journal   (Followers: 7)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 7)
Biometrical Journal     Hybrid Journal   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Lifetime Data Analysis     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)
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)
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)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 3)
Sankhya A     Hybrid Journal   (Followers: 3)
Journal of Statistical and Econometric Methods     Open Access   (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)
International Journal of Stochastic Analysis     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)
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  
Journal of the Korean Statistical Society     Hybrid Journal  

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