Non parametric maximum likelihood (npml), Advanced Statistics

Assignment Help:

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.


Related Discussions:- Non parametric maximum likelihood (npml)

Maximum likelihood estimation, Maximum likelihood estimation is an estimat...

Maximum likelihood estimation is an estimation procedure involving maximization of the likelihood or the log-likelihood with respect to the parameters. Such type of estimators is

What is the expectation of the number of tosses required, Question 1 A box...

Question 1 A box contains 20 fuses of which 5 are defective If 2 fuses are chosen together at random what is the probability that both the fuses are defective? Question 2 A c

Collective risk models, Collective risk models : The models applied to insu...

Collective risk models : The models applied to insurance portfolios which do not create direct reference to the risk characteristics of individual members of the portfolio when des

Extreme values, The biggest and smallest variate values among the sample of...

The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.

Hazard regression, Hazard regression is the procedure for modeling the haz...

Hazard regression is the procedure for modeling the hazard function which does not depend on the suppositions made in Cox's proportional hazards model, namely that the log-hazard

Latent class analysis, Latent class analysis is a technique of assessing w...

Latent class analysis is a technique of assessing whether the set of observations including q categorical variables, in specific, binary variables, consists of the number of diffe

Explain lancaster models., Lancaster models : The means of representing the...

Lancaster models : The means of representing the joint distribution of the set of variables in terms of the marginal distributions, supposing all the interactions higher than a par

Data mining, The non-trivial extraction of implicit, earlier unknown and po...

The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial inte

Define percentile, Percentile : The set or group of divisions which produce...

Percentile : The set or group of divisions which produce exactly 100 equal parts in the series of continuous values, like blood pressure, height, weight, etc. Hence a person with b

Hill-climbing algorithm, Hill-climbing algorithm is  an algorithm which is ...

Hill-climbing algorithm is  an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizin

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd