I am actually trying to better understand the distinction between mixture models and mixture distributions in my own work. You seem to say mixture models apply to a small set of models – namely regression models.
Last time, I discussed some of the advantages and disadvantages of robust estimators like the median and the MADM scale estimator, noting that certain types of datasets – like the rainfall dataset discussed last time – can cause these estimators to fail spectacularly. An extremely useful idea in working with datasets like this one is that of mixture distributions,...
. That chapter adopts the definition of an outlier presented by Barnett and Lewis in their book Outliers in Statistical Data 2nd Edition
“Our belief is that a useful measure of interestingness should generate index values that are reasonably distributed throughout...
“Our belief is that a useful measure of interestingness should generate index values that are reasonably distributed throughout...
In my last post, I discussed the use of odds ratios to characterize the association between edibility and binary mushroom characteristics for the mushrooms characterized in the UCI mushroom dataset. I did not, however, describe those co...
In my last two posts, I have used the UCI mushroom dataset to illustrate two things. The first was the use of interestingness measures to characterize categorical variables, and the second was the use of binary confidence intervals...
In my last post, I considered the UCI mushroom dataset and characterized the variables included there using four different interestingness measures. When I began drafting this post, my intention was to consider the question of how the different m...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
