Title: Estimation and Diagnostics for Partially Linear Censored
Regression Models Based on Heavy-Tailed Distributions
Maintainer: Marcela Nunez Lemus <marcela.nunez.lemus@gmail.com>
Description: It estimates the parameters of a partially linear regression censored model via maximum penalized likelihood through of ECME algorithm. The model belong to the semiparametric class, that including a parametric and nonparametric component. The error term considered belongs to the scale-mixture of normal (SMN) distribution, that includes well-known heavy tails distributions as the Student-t distribution, among others. To examine the performance of the fitted model, case-deletion and local influence techniques are provided to show its robust aspect against outlying and influential observations. This work is based in Ferreira, C. S., & Paula, G. A. (2017) <doi:10.1080/02664763.2016.1267124> but considering the SMN family.

Title: Partially Overlapping Samples t-Tests
Description: The "partially overlapping samples t-tests", for the comparison
of means for two samples which include both paired observations and independent
observations. [See Derrick, B., Russ, B., Toher, D. & White P (2017). Test
statistics for the comparison of means for two samples which include both paired
observations and independent observations. Journal of Modern Applied Statistical

Title: Partially Overlapping Samples Tests
Description: Tests for a comparison of two partially overlapping samples.
A comparison of means using the partially overlapping samples t-test:
See Derrick, Russ, Toher and White (2017), Test
statistics for the comparison of means for two samples which include
both paired observations and independent observations, Journal of
Modern Applied Statistical Methods, 16(1).
A comparison of proportions using the partially overlapping samples z-test:
See Derrick, Dobson-Mckittrick, Toher and White (2015), Test statistics
for comparing two proportions with partially overlapping samples.
Journal of Applied Quantitative Methods, 10(3).