Summarize Observations and Predictions

Summarize observations, predictions and errors in a PMop object made by makeOP, usually in the $data field of a PM_op object.

Usage

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

Arguments

object

A PMop object made by makeOP.

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.

• 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 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), and the bias- adjusted mean weighted squared prediction error (bamwspe). The mwpe is bias and the bamwspe 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

Summarize a Pmetrics Observed vs. Predicted x

See also

makeOP, PM_op

Author

Michael Neely