Describe Generalized principal components analysis, Advanced Statistics

Assignment Help:

Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is most in agreement with the data configuration. For instance, for the bivariate data, y1,y2, if the quadratic coordinate system is sought, a variable z is defined as given below:

127_generalized principal component analysis.png 
with the coefficients being set up so that the variance of z is a maximum amongst all such quadratic functions of y1 and y2.

 


Related Discussions:- Describe Generalized principal components analysis

Network sampling, Network sampling is a sampling design in which the simpl...

Network sampling is a sampling design in which the simple random sample or strati?ed sample of the sampling units is made and all observational units which are linked to any of th

Combine standard deviation, what is the combine standard deviation height f...

what is the combine standard deviation height from the follwing

Intention-to-treat analysis, Intention-to-treat analysis is the process in...

Intention-to-treat analysis is the process in which all the patients randomly allocated to a treatment in the clinical trial are analyzed together as representing that particular

Generalized additive model, The linear component ηi, de?ned just in the tra...

The linear component ηi, de?ned just in the traditional way: η i = x' 1 A monotone differentiable link function g that describes how E(Yi) = µi is related to the linear compon

Tests for heteroscedasticity, The Null Hypothesis - H0: There is no heteros...

The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1:  There is heteroscedasticity i.e. β 1 0 Reject H0 if nR2 > MTB >

Describe nuisance parameter, Nuisance parameter : The parameter of the mode...

Nuisance parameter : The parameter of the model in which there is no scienti?c interest but whose values are generally required (but in usual are unknown) to make inferences about

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

Bayesian inference, Bayesian inference : An approach to the inference based...

Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing

Dorfman scheme, An approach to investigations designed to recognize a parti...

An approach to investigations designed to recognize a particular medical condition in the large population, usually by means of a blood test, which might result in the considerable

Chebyshev''s inequality, Chebyshev's inequality: A statement about the pro...

Chebyshev's inequality: A statement about the proportion of the observations which fall within some number of the standard deviations of the mean for any of the probability distri

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