Katherine Loor

University of Campinas | UNICAMP · Instituto de Matemática, Estatística e Computação Científica (IMECC)

This paper proposes an alternative method to deal with spatio‐temporal data with censored and missing responses using the SAEM algorithm. This algorithm is a stochastic approximation of the widely used EM algorithm and is an important tool for models in which the E‐step does not have an analytic form. Besides the algorithm developed to estimate the...

It generates random numbers from a truncated multivariate elliptical distribution such as Normal , Student-t, Pearson VII, Slash, Logistic, and others by specifying the density generating function. It also computes first and second moment for some particular distributions.

This paper proposes an algorithm to generate random numbers from any member of the truncated multivariate elliptical family of distributions with a strictly decreasing density generating function. Based on the ideas of Neal (Ann stat 31(3):705–767, 2003) and Ho et al. (J Stat Plan Inference 142(1):25–40, 2012), we construct an efficient sampling me...

Data collected over time are common in applications and may contain censored or missing observations, making it difficult to use standard statistical procedures. This article proposes an algorithm to estimate the parameters of a censored linear regression model with errors serially correlated and innovations following a Student- distribution. This...

This paper proposes an algorithm to generate random numbers from any member of the truncated multivariate elliptical family of distributions with a strictly decreasing density generating function. Based on Neal (2003) and Ho et al. (2012), we construct an efficient sampling method by means of a slice sampling algorithm with Gibbs sampler steps. We...

This paper proposes an algorithm to estimate the parameters of a censored linear regression model when the regression errors are autocorrelated, and the innovations follow a Student-$t$ distribution. The Student-$t$ distribution is widely used in statistical modeling of datasets involving errors with outliers and a more substantial possibility of e...

It provides functions to estimate the parameters in spatial models with cen-sored/missing responses via the Expectation-Maximization (EM) algorithm (see Demp-ster, Laird, and Rubin (1977)<https://www.jstor.org/stable/2984875>), the Stochas-tic Approximation EM (SAEM) algorithm (see Delyon, Lavielle, and Moulines (1999)<https: //www.jstor.org/stable...

It estimates the parameters of a censored or missing data in spatio-temporal models using the SAEM algorithm (Delyon et al., 1999). This algorithm is a stochastic approximation of the widely used EM algorithm and an important tool for models in which the E-step does not have an analytic form. We also include the calculations for the observed inform...

The measurement of wealth is a matter of study of Econometrics, withinthis discipline there are various proposals for the construction of the wealth index. Inthis work a review is made on the construction method from the income approach,using proxy variables and applying the statistical technique of principal components.At the end of the article, a...