Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
R Codes For " Hypothesis Testing For An Extended Cox Model With Time-Varying Coefficients" (Biometrics), Chongzhi Di
R Codes For " Hypothesis Testing For An Extended Cox Model With Time-Varying Coefficients" (Biometrics), Chongzhi Di
Chongzhi Di
No abstract provided.
R Codes For "Multilevel Sparse Functional Principal Component Analysis" (Stat), Chongzhi Di
R Codes For "Multilevel Sparse Functional Principal Component Analysis" (Stat), Chongzhi Di
Chongzhi Di
No abstract provided.
R Code: A Non-Iterative Implementation Of Tango's Score Confidence Interval For A Paired Difference Of Proportions, Zhao Yang
Zhao (Tony) Yang, Ph.D.
For matched-pair binary data, a variety of approaches have been proposed for the construction of a confidence interval (CI) for the difference of marginal probabilities between two procedures. The score-based approximate CI has been shown to outperform other asymptotic CIs. Tango’s method provides a score CI by inverting a score test statistic using an iterative procedure. In the developed R code, we propose an efficient non-iterative method with closed-form expression to calculate Tango’s CIs. Examples illustrate the practical application of the new approach.
Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith
Windows Executable For Gaussian Copula With Nbd Margins, Michael S. Smith
Michael Stanley Smith
This is an example Windows 32bit program to estimate a Gaussian copula model with NBD margins. The margins are estimated first using MLE, and the copula second using Bayesian MCMC. The model was discussed in Danaher & Smith (2011; Marketing Science) as example 4 (section 4.2).
R Codes For "Multilevel Functional Principal Component Analysis" (Aoas), Chongzhi Di
R Codes For "Multilevel Functional Principal Component Analysis" (Aoas), Chongzhi Di
Chongzhi Di
No abstract provided.