Browse Items (9465 total)

The dynamichazard package implements state space models that can provide a computationally efficient way to model time-varying parameters in survival analysis. I cover the
models and some of the estimation methods implemented in dynamichazard, apply…

Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and
Hastie 2005) can be used to improve regression model coefficient estimation and prediction
accuracy, as well as to perform variable selection. Ordinal regression…

Causal effect identification considers whether an interventional probability distribution
can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system. While complete…

The aim of this paper is to describe the implementation and to provide a tutorial for
the R package ssmrob, which is developed for robust estimation and inference in sample
selection and endogenous treatment models. The sample selectivity issue…

This paper describes the R package cold for the analysis of count longitudinal data. In
this package marginal and random effects models are considered. In both cases estimation
is via maximization of the exact likelihood and serial dependence among…

We provide a hands-on introduction to optimized textual sentiment indexation using
the R package sentometrics. Textual sentiment analysis is increasingly used to unlock
the potential information value of textual data. The sentometrics package…

The R package skpr provides a suite of functions to generate and evaluate experimental
designs. Package skpr generates D, I, Alias, A, E, T, and G-optimal designs, and supports
custom user-defined optimality criteria, N-level split-plot designs,…

Multivariate time series observations are increasingly common in multiple fields of
science but the complex dependencies of such data often translate into intractable models
with large number of parameters. An alternative is given by first reducing…

We present mexhaz, an R package for fitting flexible hazard-based regression models
with the possibility to add time-dependent effects of covariates and to account for a twolevel hierarchical structure in the data through the inclusion of a normally…

An increasing number of time-consuming simulators exhibit a complex noise structure
that depends on the inputs. For conducting studies with limited budgets of evaluations,
new surrogate methods are required in order to simultaneously model the mean…