Displays a concise summary of an NMF-RE model fit, including dimensions, convergence, variance components, and a coefficient table following standard R regression output conventions.
Arguments
- object
An object of class
nmfre, returned bynmfre.- ci.show
Logical. If
TRUE, show confidence interval columns (defaultFALSE). Named object-first to match the package style (C.signed,X.init, ...). Legacyshow_ciis accepted via....- by
Grouping order of the coefficient rows:
"covariate"(default; list all bases for each covariate) or"basis"(list all covariates for each basis).- ...
Additional arguments (currently unused).
Examples
Y <- matrix(cars$dist, nrow = 1)
A <- rbind(intercept = 1, speed = cars$speed)
res <- nmfre(Y, A, rank = 1, maxit = 5000)
summary(res)
#> NMF-RE: Y(1,50) = X(1,1) [C(1,2) A + U(1,50)]
#> Iterations: 43 (converged, epsilon = 1e-05)
#> R-squared (cor^2): 0.9328 (XB+blup), 0.6511 (XB)
#> R-squared (uncentered): 0.9799 (XB+blup), 0.9091 (XB)
#> R-squared (centered): 0.9227 (XB+blup), 0.6511 (XB)
#>
#> Variance components:
#> sigma2 = 106.9 (residual)
#> tau2 = 120.2 (random effect)
#> lambda = 0.8888 (sigma2 / tau2)
#> ICC = 0.5294 (tau2*tr(X'X) / (tau2*tr(X'X) + sigma2*P))
#> dfU = 26.47
#>
#> Coefficients (Theta): run nmfre.inference(fit, Y, A) for SE / p-values.