plmm_format {plmmr} | R Documentation |
PLMM format: a function to format the output of a model constructed with plmm_fit
Description
PLMM format: a function to format the output of a model constructed with plmm_fit
Usage
plmm_format(fit, p, std_X_details, fbm_flag)
Arguments
fit |
A list of parameters describing the output of a model constructed with |
p |
The number of features in the original data (including constant features) |
std_X_details |
A list with 3 items:
|
fbm_flag |
Logical: is the corresponding design matrix filebacked? Passed from |
Value
A list with the components:
-
beta_vals
: the matrix of estimated coefficients on the original scale. Rows are predictors, columns are values oflambda
-
lambda
: a numeric vector of the lasso tuning parameter values used in model fitting. -
eta
: a number (double) between 0 and 1 representing the estimated proportion of the variance in the outcome attributable to population/correlation structure. -
s
: a vectof of the eigenvalues of relatedness matrixK
; seerelatedness_mat()
for details. -
U
: a matrix of the eigenvalues of relatedness matrixK
-
rot_y
: the vector of outcome values on the rotated scale. This is the scale on which the model was fit. -
linear_predictors
: the matrix resulting from the product ofstdrot_X
and the estimated coefficients on the ~rotated~ scale. -
penalty
: character string indicating the penalty with which the model was fit (e.g., 'MCP') -
gamma
: numeric value indicating the tuning parameter used for the SCAD or lasso penalties was used. Not relevant for lasso models. -
alpha
: numeric value indicating the elastic net tuning parameter. -
loss
: vector with the numeric values of the loss at each value oflambda
(calculated on the ~rotated~ scale) -
penalty_factor
: vector of indicators corresponding to each predictor, where 1 = predictor was penalized. -
ns_idx
: vector with the indices of predictors which were nonsingular features (i.e., had variation). -
iter
: numeric vector with the number of iterations needed in model fitting for each value oflambda
-
converged
: vector of logical values indicating whether the model fitting converged at each value oflambda