Description Usage Arguments Value
View source: R/Functions2.R View source: R/Functions5.R
Calculate the log transformed ascertainment correction under a univariate Q_i. Also return vi
Calculate the log transformed ascertainment correction under a univariate Q_i. Also return vi
1 2 3 4 5  | 
yi | 
 n_i-response vector  | 
xi | 
 n_i by p design matrix for fixed effects  | 
zi | 
 n_i by 2 design matric for random effects (intercept and slope)  | 
wi | 
 the pre-multiplier of yi to generate the sampling variable q_i  | 
beta | 
 mean model parameter vector  | 
sigma.vc | 
 vector of variance components on standard deviation scale  | 
rho.vc | 
 vector of correlations among the random effects. The length should be q choose 2  | 
sigma.e | 
 std dev of the measurement error distribution  | 
cutpoints | 
 cutpoints defining the sampling regions. (a vector of length 2)  | 
SampProb | 
 Sampling probabilities from within each region (vector of length 3).  | 
sigma0 | 
 std dev of the random intercept distribution  | 
sigma1 | 
 std dev of the random slope distribution  | 
rho | 
 correlation between the random intercept and slope  | 
sigmae | 
 std dev of the measurement error distribution  | 
yi | 
 n_i-response vector  | 
xi | 
 n_i by p design matrix for fixed effects  | 
zi | 
 n_i by q design matric for random effects (intercept and slope)  | 
wi | 
 the pre-multiplier of yi to generate the sampling variable q_i  | 
beta | 
 mean model parameter vector  | 
cutpoints | 
 cutpoints defining the sampling regions. (a vector of length 2)  | 
SampProb | 
 Sampling probabilities from within each region (vector of length 3).  | 
log transformed ascertainment correction
log transformed ascertainment correction
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