aout.conttab: Find $\alpha$-outliers in two-way contingency tables
Description
This is a wrapper function for aout.pois. We assume that each entry of a contingency table can be seen as a realization of a Poisson random variable. The parameter $\lambda$ of each cell can either be set by the user or estimated. Given the parameters, aout.conttab identifies $\alpha$-outliers in a given contingency table.
a matrix or data.frame. The contingency table to be examined.
param
a character string from c("ML", "L1", "MP") or a vector containing the parameters of each cell of the Poisson distribution: $\lambda$. "ML" yields the maximum likelihood estimate from the log-linear Poisson model using a suitable design matrix. "L1" yields the L1-estimate from rq.fit.fnc. "MP" yields the Median Polish estimate. If the parameter vector is given by the user, it is necessary that the contingency table was filled byrow = FALSE.
alpha
an atomic vector. Determines the maximum amount of probability mass the outlier region may contain. Defaults to 0.1.
hide.outliers
boolean. Returns the outlier-free data if set to TRUE. Defaults to FALSE.
show.estimates
boolean. Returns $\hat{\lambda}$ for each cell if set to TRUE. Defaults to FALSE.
Value
is.outlier that flags the outliers with TRUE and a vector named param containing the estimated lambdas.
References
Kuhnt, S. (2000) Ausreisseridentifikation im Loglinearen Poissonmodell fuer Kontingenztafeln unter Einbeziehung robuster Schaetzer. Ph.D. Thesis. Universitaet Dortmund, Dortmund. Fachbereich Statistik.
Kuhnt, S.; Rapallo, F.; Rehage, A. (2014) Outlier detection in contingency tables based on minimal patterns. Statistics and Computing 24 (3), 481-491.