qp_pi: Simple uncalibrated prediction intervals for quasi-Poisson...

In predint: Prediction Intervals

Simple uncalibrated prediction intervals for quasi-Poisson data

Description

qp_pi() is a helper function that is internally called by quasi_pois_pi(). It calculates simple uncalibrated prediction intervals for Poisson data with constant overdispersion (quasi-Poisson assumption).

Usage

qp_pi(
  newoffset,
  histoffset,
  lambda,
  phi,
  q = qnorm(1 - 0.05/2),
  alternative = "both",
  newdat = NULL,
  histdat = NULL,
  algorithm = NULL
)

Arguments

newoffset	number of experimental units in the future clusters
histoffset	number of experimental units in the historical clusters
lambda	overall Poisson mean
phi	dispersion parameter
q	quantile used for interval calculation
alternative	either "both", "upper" or "lower" alternative specifies, if a prediction interval or an upper or a lower prediction limit should be computed
newdat	additional argument to specify the current data set
histdat	additional argument to specify the historical data set
algorithm	used to define the algorithm for calibration if called via quasi_pois_pi(). This argument is not of interest for the calculation of simple uncalibrated intervals

Details

This function returns a simple uncalibrated prediction interval

[l,u]_m = n^*_m \hat{\lambda} \pm q \sqrt{n^*_m \hat{\phi} \hat{\lambda} + \frac{n^{*2}_m \hat{\phi} \hat{\lambda}}{\sum_h n_h}}

with n^*_m as the number of experimental units in the m=1, 2, ... , M future clusters, \hat{\lambda} as the estimate for the Poisson mean obtained from the historical data, \hat{\phi} as the estimate for the dispersion parameter and n_h as the number of experimental units per historical cluster.

The direct application of this uncalibrated prediction interval to real life data is not recommended. Please use the quasi_pois_pi_pi() functions for real life applications.

Value

qp_pi returns an object of class c("predint", "quasiPoissonPI").

Examples

# Prediction interval
qp_pred <- qp_pi(newoffset=3, lambda=3, phi=3, histoffset=1:9, q=qnorm(1-0.05/2))
summary(qp_pred)

predint documentation built on May 29, 2024, 12:28 p.m.