Hugo Gasca-Aragon

Hugo Gasca-Aragon

4 packages on CRAN

dwlm

cran
99.99th

Percentile

This linear model solution is useful when both predictor and response have associated uncertainty. The doubly weights linear model solution is invariant on which quantity is used as predictor or response. Based on the results by Reed(1989) <doi:10.1119/1.15963> and Ripley & Thompson(1987) <doi:10.1039/AN9871200377>.

gconsensus

cran
99.99th

Percentile

An implementation of the International Bureau of Weights and Measures (BIPM) generalized consensus estimators used to assign the reference value in a key comparison exercise. This can also be applied to any interlaboratory study. Given a set of different sources, primary laboratories or measurement methods this package provides an evaluation of the variance components according to the selected statistical method for consensus building. It also implements the comparison among different consensus builders and evaluates the participating method or sources against the consensus reference value. Based on a diverse set of references, Graybill-Deal (1959) <doi:10.2307/2527652>, DerSimonian-Laird (1986) <doi:10.1016/0197-2456(86)90046-2>, Vangel-Ruhkin (1999) <doi:10.1111/j.0006-341X.1999.00129.x>, for a complete list of references look at the reference section in the package documentation.

ggmr

cran
99.99th

Percentile

Implements the generalized Gauss Markov regression, this is useful when both predictor and response have uncertainty attached to them and also when covariance within the predictor, within the response and between the predictor and the response is present. Base on the results published in guide ISO/TS 28037 (2010) <https://www.iso.org/standard/44473.html>.

99.99th

Percentile

Implements the Gaussian method of first and second order, the Kragten numerical method and the Monte Carlo simulation method for uncertainty estimation and analysis.