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)

Please answer this question, How large would the sample need to be if we ar...

How large would the sample need to be if we are to pick a 95% confidence level sample: (i) From a population of 70; (ii) From a population of 450; (iii) From a population of 1000;

Hypergeometric distribution, Hypergeometric distribution is t he probabili...

Hypergeometric distribution is t he probability distribution related with the sampling without replacement from the population of finite size. If the population comprises of r ele

Explain markers of disease progression, Markers of disease progression : Qu...

Markers of disease progression : Quantities which form a general monotonic series throughout the course of the disease and assist with its modelling. In uasual such quantities are

Baddeley''smetric, Baddeley'smetric : A manner of measuring the 'error' in ...

Baddeley'smetric : A manner of measuring the 'error' in the image processing technique or method. The metric is derived using the fundamental theory from the stochastic geometry an

Sequencing problem, when there is tie in sequencing then what we do

when there is tie in sequencing then what we do

Reciprocal transformation, Reciprocal transformation is a transformation o...

Reciprocal transformation is a transformation of the form y =1/x, which is specifically useful for certain types of variables. Resistances, for instance, become conductances, and

Copulas, Invariant transformations to combine marginal probability function...

Invariant transformations to combine marginal probability functions to form multivariate distributions motivated by the need to enlarge the class of multivariate distributions beyo

Window estimates, Window estimates is a term which occurs in the context o...

Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights

Categorizing continuous variables, Categorizing continuous variables : A pr...

Categorizing continuous variables : A practice which involves the conversion of the continuous variables into the series of the categories, which is common in the field of medical

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