plot.initgmf: Plot diagnostics for an initialized GMF model

In sgdGMF: Estimation of Generalized Matrix Factorization Models via Stochastic Gradient Descent

Plot diagnostics for an initialized GMF model

Description

Plots (one of) six diagnostics to graphically analyze the marginal and conditional distribution of the residuals of a GMF model. Currently, the following plots are available: residuals against observation indices, residuals agains fitted values, absolute square-root residuals against fitted values, histogram of the residuals, residual QQ-plot, residual ECDF-plot.

Usage

## S3 method for class 'initgmf'
plot(
  x,
  ...,
  type = c("res-idx", "res-fit", "std-fit", "hist", "qq", "ecdf"),
  resid = c("deviance", "pearson", "working", "response", "link"),
  subsample = FALSE,
  sample.size = 500,
  partial = FALSE,
  normalize = FALSE,
  fillna = FALSE
)

Arguments

x	an object of class initgmf
...	further arguments passed to or from other methods
type	the type of plot which should be returned
resid	the type of residuals which should be used
subsample	if TRUE, computes the residuals over o small fraction of the data
sample.size	the dimension of the sub-sample which should be used
partial	if TRUE, computes the partial residuals
normalize	if TRUE, standardizes the residuals column-by-column
fillna	if TRUE, fills the NA values with 0

Value

A ggplot object showing the selected diagnostic plot.

See Also

plot.sgdgmf.

Examples

# Load the sgdGMF package
library(sgdGMF)

# Generate data from a Poisson model
data = sim.gmf.data(n = 100, m = 20, ncomp = 5, family = poisson())

# Fit a GMF model
init = sgdgmf.init(data$Y, ncomp = 3, family = poisson())

# Plot the residual-based GMF diagnostics
plot(init, type = "res-fit") # Residuals vs fitted values
plot(init, type = "std-fit") # Abs-sqrt-transformed residuals vs fitted values
plot(init, type = "qq") # Residual QQ-plot
plot(init, type = "hist") # Residual histogram

sgdGMF documentation built on April 3, 2025, 7:37 p.m.