OutlierRegression: Finding outliers of a sigle variable (y) by a regression...

In statisticsnorway/Kostra: Functions for Kostra

Finding outliers of a sigle variable (y) by a regression model using a single explanatory variable (x).

Description

outliers are found by using a limit for studentized residuals.

Usage

OutlierRegression(
  data,
  idName = names(data)[1],
  strataName = NULL,
  xName = names(data)[3],
  yName = names(data)[4],
  method = "ordinary",
  limitModel = 2.5,
  limitIterate = 4.5
)

OutlierRegressionMicro(...)

OutlierRegressionTall(..., iD = TalliD())

OutlierRegressionWide(
  ...,
  addName = WideAddName(),
  sep = WideSep(),
  idNames = c("", "strata", ""),
  addLast = FALSE
)

Arguments

data	Input data set of class data.frame
idName	Name of id-variable(s)
strataName	Name of starta-variable. Single strata when NULL (default)
xName	Name of x-variable
yName	Name of y-variable
method	The method (model and weight) coded as a string: "ordinary" (default), "ratio", "noconstant", "mean" or "ratioconstant".
limitModel	Studentized residuals limit. Above limit -> outlier.
limitIterate	Studentized residuals limit for iterative calculation of studentized residuals.

Details

This function is related to ImputeRegression and the structure and the names of output are very similar. Note that missing values of x are allowed here.

Value

Output of OutlierRegression is a list of two data frames. The micro data frame has as many rows as input and aggregates data frame has one row for each strata. The individual variables are:

micro consists of the following elements:

id	id from input
x	The input x variable
y	The input y variable
strata	The input strata variable (can be NULL)
outlier	Dummy variable: outlier (1) or not (0).
category123	The three imputation groups: representative (1), correct but not representative (2), wrong (3).
yHat	Fitted values
rStud	The studentized residuals from last iteration
dffits	The DFFITS statistic from last iteration
hii	The leverages (diagonal elements of hat matrix) from last iteration
leaveOutResid	The outside-model residual from last iteration
limLo	-limitModel
limUp	limitModel

aggregates consists of the following elements:

N	Number of observations in each strata
coef	The final first model coefficient
coefB	The final second model coefficient or zeros when only one coefficient in model.
nModel	The final number of observations in model.
sigmaHat	The final square root of the estimated variance parameter

Output of OutlierRegressionMicro is the single data frame micro above.

Output of OutlierRegressionTall and OutlierRegressionWide are similiar to the functions in ImputeRegression.

Author(s)

Øyvind Langsrud

Examples

z = cbind(id=1:34,KostraData("ratioTest")[,c(3,1,2)])
OutlierRegression(z,strataName="k")
OutlierRegressionMicro(z,strataName="k")
OutlierRegressionTall(z,strataName="k")
OutlierRegressionWide(z,strataName="k")

rateData <- KostraData("rateData")               # Real Kostra data set
w <- rateData$data[, c(17,19,16,5)]              # Data with id, strata, x and y
w <- w[is.finite(w[,"Ny.kostragruppe"]), ]       # Remove Longyearbyen
w[w[,"Ny.kostragruppe"]>13,"Ny.kostragruppe"]=13 # Combine small strata
OutlierRegression(w, strataName = names(w)[2], method="ratio")

statisticsnorway/Kostra documentation built on Nov. 2, 2024, 6:40 p.m.