GOF_model {bootGOF} | R Documentation |
Convenience function for creating a GOF-test for statistical models
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()