mc_bias_corrected_std
(Package: mcglm) :
Bias-corrected Standard Error for Regression Parameters
Compute bias-corrected standard error for regression parameters in the context of clustered observations for an object of mcglm class. It is also robust and has improved finite sample properties.
● Data Source:
CranContrib
● Keywords:
● Alias: mc_bias_corrected_std
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mc_sic
(Package: mcglm) :
Score Information Criterion - Regression
Compute the score information criterion (SIC) for an object of mcglm class. The SIC is useful for selecting the components of the linear predictor. It can be used to construct an stepwise covariate selection.
● Data Source:
CranContrib
● Keywords:
● Alias: mc_sic
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The mc_link_function is a customized call of the make.link function.
● Data Source:
CranContrib
● Keywords:
● Alias: mc_cauchit, mc_cloglog, mc_identity, mc_inverse, mc_invmu2, mc_link_function, mc_log, mc_logit, mc_loglog, mc_probit, mc_sqrt
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plogLik
(Package: mcglm) :
Gaussian Pseudo-loglikelihood
Extract the Gaussian pseudo-loglikelihood (plogLik) value for objects of mcglm class.
● Data Source:
CranContrib
● Keywords:
● Alias: plogLik
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mc_sandwich
(Package: mcglm) :
Matrix product in sandwich form
The function mc_sandwich is just an auxiliar function to compute product matrix in the sandwich form bord1 * middle * bord2. An special case appears when computing the derivative of the covariance matrix with respect to the power parameter. Always the bord1 and bord2 should be diagonal matrix. If it is not true, this product is too slow.
● Data Source:
CranContrib
● Keywords: internal
● Alias: mc_multiply, mc_multiply2, mc_sandwich, mc_sandwich_cholesky, mc_sandwich_negative, mc_sandwich_power
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mc_core_pearson
(Package: mcglm) :
Core of the Pearson estimating function.
Core of the Pearson estimating function.
● Data Source:
CranContrib
● Keywords: internal
● Alias: mc_core_pearson
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mc_robust_std
(Package: mcglm) :
Robust Standard Error for Regression Parameters
Compute robust standard error for regression parameters in the context of clustered observations for an object of mcglm class.
● Data Source:
CranContrib
● Keywords:
● Alias: mc_robust_std
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covprod
(Package: mcglm) :
Cross variability matrix
Compute the cross-covariance matrix between covariance and regression parameters. Equation (11) of Bonat and Jorgensen (2015).
● Data Source:
CranContrib
● Keywords: internal
● Alias: covprod
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confint.mcglm
(Package: mcglm) :
Confidence Intervals for Model Parameters
Computes confidence intervals for parameters in a fitted mcglm model.
● Data Source:
CranContrib
● Keywords:
● Alias: confint.mcglm
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mc_compute_rho
(Package: mcglm) :
Autocorrelation Estimates
Compute autocorrelation estimates based on a fitted model using the mc_car structure. The mcglm approach fits models using a linear covariance structure, but in general in this parametrization for spatial models the parameters have no simple interpretation in terms of spatial autocorrelation. The function mc_compute_rho computes the autocorrelation based on a fitted model.
● Data Source:
CranContrib
● Keywords:
● Alias: mc_compute_rho
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