GOF_model: Convenience function for creating a GOF-test for statistical...

In bootGOF: Bootstrap Based Goodness-of-Fit Tests

Description

Simplifies the creation of an instance of GOF_model_test, the actual work horse for performing a goodness-of-fit-test.

Usage

GOF_model(
  model,
  data,
  nmb_boot_samples,
  simulator_type,
  y_name,
  Rn1_statistic,
  gof_model_resample_class = GOF_model_resample,
  gof_model_test_class = GOF_model_test
)

Arguments

model	of class 'lm' or 'glm'. Caution with MASS::glm.nb, see vignette 'New-Models' for more details.
data	see GOF_model_test
nmb_boot_samples	see GOF_model_test
simulator_type	either "parameteric" or "semi_parameteric_rademacher"
y_name	see GOF_model_test
Rn1_statistic	see GOF_model_test
gof_model_resample_class	no need to change this parameter. Here the class used for resampling the model (GOF_model_resample) is injected. This parameter simply makes it easier to test the convenience function properly.
gof_model_test_class	no need to change this parameter. Here the class used for performing the GOF test (GOF_model_test) is injected. This parameter simply makes it easier to test the convenience function properly.

Value

instance of GOF_model_test

Examples

set.seed(1)
N <- 100
X1 <- rnorm(N)
X2 <- rnorm(N)
d <- data.frame(
  y = rpois(n = N, lambda = exp(4 + X1 * 2 + X2 * 6)),
  x1 = X1,
  x2 = X2)
fit <- glm(y ~ x1, data = d, family = poisson())
mt <- GOF_model(
  model = fit,
  data = d,
  nmb_boot_samples = 100,
  simulator_type = "parametric",
  y_name = "y",
  Rn1_statistic = Rn1_KS$new())
mt$get_pvalue()
fit <- glm(y ~ x1 + x2, data = d, family = poisson())
mt <- GOF_model(
  model = fit,
  data = d,
  nmb_boot_samples = 100,
  simulator_type = "parametric",
  y_name = "y",
  Rn1_statistic = Rn1_KS$new())
mt$get_pvalue()

bootGOF documentation built on June 24, 2021, 9:12 a.m.