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Open Journal of Statistics (OJS) is an international journal dedicated to the latest advancements in statistics. The goal of this journal is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of statistics. All…
Bruno P. Klaholz, 1 1, 1 1, 1 1
Heterogeneity of biological samples is usually considered a major obstacle for three-dimensional (3D) structure determination of macromolecular complexes. Heterogeneity may occur at the level of composition or conformational variability of complexes and affec…
Zanhua Yin, Fang Liu
In this article, we develop estimation approaches for nonparametric multiple regression measurement error models when both independent validation data on covariables and primary data on the response variable and surrogate covariables are available. An estimat…
Claudio Morana, 1 1
The paper introduces a new Frequentist model averaging estimation procedure, based on a stacked OLS estimator across models, implementable on cross-sectional, panel, as well as time series data. The proposed estimator shows the same optimal properties of the…
Pamphile Mezui-Mbeng
In this paper, we generalize the proof of the Cochran statistic in the case of an ANOVA two ways structure that asymptotically follows a Chi-2. While construction of homogeneity statistics test usually resorts to the determination of the covariance matrix and…
Matthew A. Corsetti, Ernest Fokoué
Nonnegative matrix factorization (NMF) is a relatively new unsupervised learning algorithm that decomposes a nonnegative data matrix into a parts-based, lower dimensional, linear representation of the data. NMF has applications in image processing, text minin…
Mingxing Zhang, Jiannan Qiao, Huawei Yang, Zixin Liu
This paper simultaneously investigates variable selection and imputation estimation of semiparametric partially linear varying-coefficient model in that case where there exist missing responses for cluster data. As is well known , commonly used approach to de…
Michael Olusegun Akinwande, Hussaini Garba Dikko, Agboola Samson
Suppression effect in multiple regression analysis may be more common in research than what is currently recognized. We have reviewed several literatures of interest which treats the concept and types of suppressor variables. Also, we have highlighted systema…
M. O. Adenomon, V. A. Michael, O. P. Evans
Forecasts can either be short term, medium term or long term. In this work we considered short term forecast because of the problem of limited data or time series data that is often encounter in time series analysis. This simulation study considered the perfo…
F. Brouers
In this paper, we recall for physicists how it is possible using the principle of maximization of the Boltzmann-Shannon entropy to derive the Burr-Singh-Maddala (BurrXII) double power law probability distribution function and its approximations (Pareto, loglo…
Azhari A. Elhag, Omar I. O. Ibrahim, Mohamed A. El-Sayed, Gamal A. Abd-Elmougod
This paper deals with the Bayesian inferences of unknown parameters of the progressively Type II censored Weibull-geometric (WG) distribution. The Bayes estimators cannot be obtained in explicit forms of the unknown parameters under a squared error loss funct…
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Open Journal of Statistics (OJS) is an international journal dedicated to the latest advancements in statistics. The goal of this journal is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of statistics. All… All articles are open access under a CC BY 4.0 licence, with authors retaining copyright.
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