binning: Binning methods for Visual Predictive Check (VPC)

In tidyvpc: VPC Percentiles and Prediction Intervals

Binning methods for Visual Predictive Check (VPC)

Description

This function executes binning methods available in classInt i.e. "jenks", "kmeans", "sd", "pretty", "pam", "kmeans", "hclust", "bclust", "fisher", and "dpih". You may also bin directly on x-variable or alternatively specify "centers" or "breaks". For explanation of binning methods see classIntervals.

Usage

binning(o, ...)

## S3 method for class 'tidyvpcobj'
binning(
  o,
  bin,
  data = o$data,
  xbin = "xmedian",
  centers,
  breaks,
  nbins,
  altx,
  stratum = NULL,
  by.strata = TRUE,
  ...
)

Arguments

o	A tidyvpcobj.
...	Other arguments to include for classIntervals. See ... usage for style in ?classIntervals.
bin	Character string indicating binning method or unquoted variable name if binning on x-variable.
data	Observed data supplied in observed() function.
xbin	Character string indicating midpoint type for binning.
centers	Numeric vector of centers for binning. Use bin = "centers", if supplying centers.
breaks	Numeric vector of breaks for binning. Use bin = "breaks", if supplying breaks.
nbins	Numeric number indicating the number of bins to use.
altx	Unquoted variable name in observed data for alternative x-variable binning.
stratum	List indicating the name of stratification variable and level, if using different binning methods by strata.
by.strata	Logical indicating whether binning should be performed by strata.

Value

Updates tidyvpcobj with data.frame containing bin information including left/right boundaries and midpoint, as specified in xbin argument.

See Also

observed simulated censoring predcorrect stratify binless vpcstats

Examples

require(magrittr)

 # Binning on x-variable NTIME
vpc <- observed(obs_data, x=TIME, y=DV) %>%
    simulated(sim_data, y=DV) %>%
    binning(bin = NTIME) %>%
    vpcstats()
    
 # Binning using ntile and xmean for midpoint
vpc <- observed(obs_data, x=TIME, y=DV) %>%
    simulated(sim_data, y=DV) %>%
    binning(bin = "ntile", nbins = 8, xbin = "xmean") %>%
    vpcstats()
    
 # Binning using centers
vpc <- observed(obs_data, x=TIME, y=DV) %>%
    simulated(sim_data, y=DV) %>%
    binning(bin = "centers", centers = c(1,3,5,7)) %>%
    vpcstats()
        
 # Different Binning for each level of Strata
vpc <- observed(obs_data, x=TIME, y=DV) %>%
    simulated(sim_data, y=DV) %>%
    stratify(~ GENDER) %>%
    binning(stratum = list(GENDER = "M"), bin = "jenks", nbins = 5, by.strata = TRUE) %>%
    binning(stratum = list(GENDER = "F"), bin = "pam", nbins = 4, by.strata = TRUE) %>%
    vpcstats()
    
 # Binning Categorical DV using rounded time variable
  
  vpc <- observed(obs_cat_data, x = agemonths, y = zlencat ) %>%
      simulated(sim_cat_data, y = DV) %>%
      binning(bin = round(agemonths, 0)) %>%
      vpcstats(vpc.type = "categorical")

tidyvpc documentation built on Oct. 29, 2022, 1:13 a.m.