The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Build Status lifecycle Project Status: Active – The project has reached a stable, usable state and is being actively developed. CRAN_Status_Badge_version_ago metacran downloads license

bootGOF

Bootstrap based goodness-of-fit tests for (linear) models. Assume you have fitted a statistical model, e.g. classical linear model or generalized linear model or a model that follows (Y = m(^X) + ). This package allows to perform a rigorous statistical test to check if the chosen model family is correct.

Example

First we generate a data-set in order to apply the package.

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)

Note that both covariates influence the dependent variable (Y). Taking only one of the covariates into account obviously leads to a model family that is not correct and the GOF-test should reveal that:

fit <- glm(y ~ x1, data = d, family = poisson())

library(bootGOF)
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()
#> [1] 0

On the other hand assuming the correct model family should in general not be rejected by the GOF-test:

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()
#> [1] 0.61

…

Installation

You can install it from CRAN

install.packages("bootGOF")

or github

devtools::install_github("MarselScheer/bootGOF")

sessionInfo

sessionInfo()
#> R version 4.0.0 (2020-04-24)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 20.04 LTS
#> 
#> Matrix products: default
#> BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=C             
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices datasets  utils     methods   base     
#> 
#> other attached packages:
#> [1] bootGOF_0.1.0     badgecreatr_0.2.0
#> 
#> loaded via a namespace (and not attached):
#>  [1] digest_0.6.25   R6_2.4.1        backports_1.1.8 git2r_0.27.1   
#>  [5] magrittr_1.5    evaluate_0.14   rlang_0.4.10    stringi_1.4.6  
#>  [9] renv_0.10.0     checkmate_2.0.0 rmarkdown_2.3   tools_4.0.0    
#> [13] stringr_1.4.0   xfun_0.15       yaml_2.2.1      compiler_4.0.0 
#> [17] htmltools_0.5.0 knitr_1.29

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.