predcorrect | R Documentation |
Specify prediction variable for pcVPC.
predcorrect(o, ...)
## S3 method for class 'tidyvpcobj'
predcorrect(o, pred, data = o$data, ..., log = FALSE)
o |
A |
... |
Other arguments to include. |
pred |
Prediction variable in observed data. |
data |
Observed data supplied in |
log |
Logical indicating whether DV was modeled in logarithmic scale. |
Updates tidyvpcobj
with required information to performing prediction correction, which includes the predcor
logical indicating whether
prediction corrected VPC is to be performed, the predcor.log
logical indicating whether the DV is on a log-scale, and the pred
prediction
column from the original data.
observed
simulated
censoring
stratify
binning
binless
vpcstats
require(magrittr)
obs_data <- obs_data[MDV == 0]
sim_data <- sim_data[MDV == 0]
# Add PRED variable to observed data from first replicate of
# simulated data
obs_data$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()
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