tidyvpc (version 1.5.2)

binning: 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", "dpih", "box", "headtails", and "maximum". 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 tidyvpcobj
binning(
  o,
  bin,
  data = o$data,
  xbin = "xmedian",
  centers,
  breaks,
  nbins,
  altx,
  stratum = NULL,
  by.strata = TRUE,
  ...
)

Value

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

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.

See Also

observed simulated censoring predcorrect stratify binless vpcstats

Examples

# \donttest{
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 = "kmeans", 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")
# }