quantregGrowth - Non-Crossing Additive Regression Quantiles and Non-Parametric Growth Charts
Fits non-crossing regression quantiles as a function of linear covariates and multiple smooth terms, including varying coefficients, via B-splines with L1-norm difference penalties. Random intercepts and variable selection are allowed via the lasso penalties. The smoothing parameters are estimated as part of the model fitting, see Muggeo and others (2021) <doi:10.1177/1471082X20929802>. Monotonicity and concavity constraints on the fitted curves are allowed, see Muggeo and others (2013) <doi:10.1007/s10651-012-0232-1>, and also <doi:10.13140/RG.2.2.12924.85122> or <doi:10.13140/RG.2.2.29306.21445> some code examples.
Last updated 9 months ago
2.82 score 1 stars 1 dependents 22 scripts 642 downloadslogNormReg - log Normal Linear Regression
Functions to fits simple linear regression models with log normal errors and identity link, i.e. taking the responses on the original scale. See Muggeo (2018) <doi:10.13140/RG.2.2.18118.16965>.
Last updated 3 years ago
1.62 score 1 dependents 14 scripts 408 downloadscumSeg - Change Point Detection in Genomic Sequences
Estimation of number and location of change points in mean-shift (piecewise constant) models. Particularly useful (but not confined) to model genomic sequences of continuous measurements.
Last updated 5 years ago
1.53 score 1 stars 17 scripts 297 downloads