Summarize Observations and Predictions

Summarize a Pmetrics Observed vs. Predicted object

Usage

# S3 method for class 'PM_op'
summary(
  object,
  digits = max(3, getOption("digits") - 3),
  pred.type = "post",
  icen = "median",
  outeq = 1,
  ...
)

Arguments

object: A PM_op object
digits: Integer, used for number of digits to print.
pred.type: Either 'post' for a posterior object or 'pop' for a population object. Default is 'post'.
icen: Can be either "median" for the predictions based on medians of pred.type parameter value distributions, or "mean". Default is "median".
outeq: Output equation number. Default is 1.
...: Not used.

Value

A list with three elements of class summary.PM_op.

sumstat A data frame with the minimum, first quartile, median, third quartile, maximum, mean and standard deviation for times, observations and predictions in x.
pe A named vector with mean prediction error (mpe), the mean weighted prediction error (mwpe), the percent mean weighted prediction error (percent_mwpe), the mean squared prediction error (mspe), root mean sqaured error (rmse), percent root mean squared error (percent_rmse), the mean weighted squared prediction error (mwspe), the bias-adjusted mean squared prediction error (bamspe), the bias- adjusted mean weighted squared prediction error (bamwspe), the percent root mean bias- adjusted weighted squared prediction error (percent_rmbawspe). The percent_mwpe is bias and the percent_rmbawspe is imprecision on plots of PM_op objects.
wtd.t A list of 6 elements based on a t test that the weighted mean prediction bias is different than zero

estimate: the weighted mean of the prediction bias for each observation
se: the standard error of the estimate
conf.int: the 95% confidence interval of the mean
statistic: the t statistic of the standardized difference between mean and zero
df: degrees of freedom equal to number of observations minus one
p.value: the probability that the weighted mean is different than zero

Details

This is a function usually called by the $summary() method for PM_op objects within a PM_result to summarize observations, predictions and errors. The function can be called directly on a PM_op object. See examples.

Author

Michael Neely

Examples

if (FALSE) { # \dontrun{
NPex$op$summary() # preferred
summary(NPex$op) # alternative
} # }