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Non parametric maximum likelihood (NPML) is a likelihood approach which does not need the specification of the full parametric family for the data. Usually, the non parametric maximum likelihood is a multinomial likelihood on a sample. Simple examples comprise the empirical cumulative distribution function and the product-limit estimator. It is also used to relax the parametric assumptions regarding random effects in the multilevel models. It is losely related to the empirical likelihood.
Regression line drawn as y= c+ 1075x ,when x was2, and y was 239,given that y intercept was 11. Calculate the residual ?
historigrams and histogram
I have a problem I am trying to solve. An oil company thinks that there is a 60% chance that there is oil in the land they own. Before drilling they run a soil test. When there is
Probability judgements : Human beings often require assessing the probability which some event will occur and accuracy of these probability judgements often determines success of o
Cluster sampling : A method or technique of sampling in which the members of the population are arranged in groups (called as 'clusters'). A number of clusters are selected at the
Help on my test preparation . .
A metal fabrication process uses a die-cast metal fastener at a uniform rate of 300 units per year. Currently, this item is currently purchased from an external supplier at a unit
hello I have a dataset including both categorical & numerical variable for market segmentation.how can i cluster them via k-means in matlab? thank you
Kaiser's rule is the rule frequently used in the principal components analysis for selecting the suitable the number of components. When the components are derived from correlati
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