predPow: Statistical analysis of a model results compared to observations.

Description

Determines the model calibration or its prediction power. The statistical analysis is done with the observed values and their related prediction only, as no data about the model used to calculate the prediction is available.

Usage

calibPow(data, obs = "observed", pred = "predicted",  nu = 0, round = 4, extOut = FALSE, extOutFile = NULL) predPow(data, obs = "observed", pred = "predicted",  obs_mean = NULL, nu = 0, round = 4, extOut = FALSE,  extOutFile = NULL)

Arguments

data

A data frame that contains at least two columns containing the observations and their predictions. The data frame can be extended e.g. by a column that specifies the individual mean of the observed values $y_{mean}^{N-k,i}$.

obs

The name of the column that contains the observations

pred

The name of the column that contains the predictions

obs_mean

The mean of the observations $y_{mean}^{N-k,i}$. Can be either a string that names the actual column or the column itself

The degrees of freedom used for rmse calculation, DEFAULT: 0

round

The rounding value used in the output, DEFAULT: 4

extOut

Extended output, DEFAULT: FALSE If extOutFile is not specified, write to stdout()

extOutFile

Write extended output into file (implies extOut = TRUE), DEFAULT: NULL

Value

Returns an object of class "q2". It contains information about the model calibration or its prediction performance.

Details

data contains the observation and the its predictions calculated with model M. calibPow() Alias: calibrationPower() The calibration power of model M is calculated with data. predPow() Alias: predictionPower() The prediction power of model M is calculated with data.

Examples

Run this code

  require(methods)
  require(stats)
  library(cvq2)
  
  data(cvq2.sample.C)
  result <- calibPow( cvq2.sample.C )
  result
  
  data(cvq2.sample.D)
  result <- predPow( cvq2.sample.D, obs_mean="observed_mean" )
  result