| predcorrect {tidyvpc} | R Documentation |
Prediction corrected Visual Predictive Check (pcVPC)
Description
Specify prediction variable for pcVPC.
Usage
predcorrect(o, ...)
## S3 method for class 'tidyvpcobj'
predcorrect(o, pred, data = o$data, ..., log = FALSE)
Arguments
o |
A |
... |
Other arguments to include. |
pred |
Prediction variable in observed data. |
data |
Observed data supplied in |
log |
Logical indicating whether DV was modeled in logarithmic scale. |
Value
Updates tidyvpcobj with required information to performing prediction correction, which includes the predcor logical indicating whether
prediction corrected VPC is to be performed, the predcor.log logical indicating whether the DV is on a log-scale, and the pred prediction
column from the original data.
See Also
observed simulated censoring stratify binning binless vpcstats
Examples
require(magrittr)
obs_data <- obs_data[MDV == 0]
sim_data <- sim_data[MDV == 0]
# Add PRED variable to observed data from first replicate of
# simulated data
obs_data$PRED <- sim_data[REP == 1, PRED]
vpc <- observed(obs_data, x=TIME, y=DV) %>%
simulated(sim_data, y=DV) %>%
binning(bin = NTIME) %>%
predcorrect(pred=PRED) %>%
vpcstats()
# For binless loess prediction corrected, use predcorrect() before
# binless() and set loess.ypc = TRUE
vpc <- observed(obs_data, x=TIME, y=DV) %>%
simulated(sim_data, y=DV) %>%
predcorrect(pred=PRED) %>%
binless(loess.ypc = TRUE) %>%
vpcstats()
[Package tidyvpc version 1.5.1 Index]