Computational Statistics

Công bố khoa học tiêu biểu

* Dữ liệu chỉ mang tính chất tham khảo

Sắp xếp:  
A genetic algorithm for designing microarray experiments
Computational Statistics - Tập 31 - Trang 409-424 - 2015
A. H. M. Mahbub Latif, Edgar Brunner
Heuristic techniques of optimization can be useful in designing complex experiments, such as microarray experiments. They have advantages over the traditional methods of optimization, particularly in situations where the search space is discrete. In this paper, a search procedure based on a genetic algorithm is proposed to find optimal (efficient) designs for both one- and multi-factor experiments...... hiện toàn bộ
Dynamic Link Library for Statistical Analysis and Its Excel Interface
Computational Statistics - - 2002
Akinobu Takeuchi, Hiroshi Yadohisa, Kazunori Yamaguchi, Michiko Watanabe, Chooichiro Asano
Unsupervised learning on U.S. weather forecast performance
Computational Statistics - Tập 38 - Trang 1193-1213 - 2023
Chuyuan Lin, Ying Yu, Lucas Y. Wu, Jiguo Cao
Nowadays, climate events and weather predictions have a huge impact on human activities. To understand the accuracy of weather prediction, we applied the functional principal component analysis (FPCA) method to investigate the main pattern of variance within the U.S. weather prediction error over a period of 3 years. We further grouped the states in the U.S. based on their similarity in weather fo...... hiện toàn bộ
The 8-parameter Fisher–Bingham distribution on the sphere
Computational Statistics - Tập 36 - Trang 409-420 - 2020
Tianlu Yuan
The Fisher–Bingham distribution ( $$\mathrm {FB}_8$$ ) is an eight-parameter family of probability density functions (PDF) on the unit sphere that, under certain conditions, reduce to spherical analogues of bivariate normal PDFs. Due to difficulties in its interpretation and estimation, applications...... hiện toàn bộ
Interacting with local and remote data repositories using the stashR package
Computational Statistics - Tập 24 Số 2 - Trang 247-254 - 2009
Sandrah P. Eckel, Roger D. Peng
Bayesian inference on longitudinal-survival data with multiple features
Computational Statistics - Tập 32 - Trang 845-866 - 2016
Tao Lu
The modeling of longitudinal and survival data is an active research area. Most of researches focus on improving the estimating efficiency but ignore many data features frequently encountered in practice. In this article, we develop a joint model that concurrently accounting for longitudinal-survival data with multiple features. Specifically, our joint model handles skewness, limit of detection, m...... hiện toàn bộ
Investigating GQL-based inferential approaches for non-stationary BINAR(1) model under different quantum of over-dispersion with application
Computational Statistics - Tập 34 - Trang 1275-1313 - 2018
N. Mamode Khan, Y. Sunecher, V. Jowaheer, M. M. Ristic, M. Heenaye-Mamode Khan
In particular, this paper addresses solutions to the computational challenges encountered in estimating parameters in non-stationary over-dispersed bivariate integer-valued autoregressive of order 1 (BINAR(1)) model with Negative Binomial (NB) innovations. In this BINAR(1) model, the cross-correlation is induced through the paired NB innovations which follows a recently introduced bivariate NB mod...... hiện toàn bộ
Row–column interaction models, with an R implementation
Computational Statistics - Tập 29 - Trang 1427-1445 - 2014
Thomas W. Yee, Alfian F. Hadi
We propose a family of models called row–column interaction models (RCIMs) for two-way table responses. RCIMs apply some link function to a parameter (such as the cell mean) to equal a row effect plus a column effect plus an optional interaction modelled as a reduced-rank regression. What sets this work apart from others is that our framework incorporates a very wide range of statistical models, e...... hiện toàn bộ
Computations for the familial analysis of binary traits
Computational Statistics - Tập 20 - Trang 439-448 - 2005
Harry Joe, A. H. M. Mahbub-ul Latif
For familial aggregation of a binary trait, one method that has been used is the GEE2 (generalized estimating equation) method corresponding to a multivariate logit model. We solve the complex estimating equations for the GEE2 method using an automatic differentiation software which computes the derivatives of a function numerically using the chain rule of the calculus repeatedly on the elementary...... hiện toàn bộ
Tổng số: 1,140   
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 10