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

Last observation carried forward, Last observation carried forward is a te...

Last observation carried forward is a technique for replacing the observations of the patients who drop out of the clinical trial carried out over a time period. It consists of su

Frequency polygon, It is the diagram used to display the values graphically...

It is the diagram used to display the values graphically in a frequency distribution. The frequencies are graphed as an ordinate against the class mid-points as abscissae. The p

Bartlett''s test for variances, Bartlett's test for variances : A test for ...

Bartlett's test for variances : A test for equality of the variances of the number (k)of the populations. The test statistic can be given as follows   where s square is an

Best subsets regression, In the time series plot and scatter graphs there w...

In the time series plot and scatter graphs there were many outliers that were clearly visible. These have been removed to identify if they were influential or had high leverage and

Adjusted r-squared, R-squared is regarded as the coefficient of determinati...

R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also

Glejser test, Glejser test is the test for the heteroscedasticity in the e...

Glejser test is the test for the heteroscedasticity in the error terms of the regression analysis which involves regressing the absolute values of the regression residuals for the

Explain Genetic algorithms, Genetic algorithms: The optimization events mo...

Genetic algorithms: The optimization events motivated by the biological analogies. The prime idea is to try to mimic the 'survival of the fittest' rule of the genetic mutation in

Effect sparsity, The term which is used in the industrial experimentation, ...

The term which is used in the industrial experimentation, where there is commonly a large set of candidate factors believed to have the possible significant influence on the respon

Clinical vs. statistical significance, Clinical vs. statistical significanc...

Clinical vs. statistical significance : The distinction among results in terms of their possible clinical importance rather than simply in terms of their statistical importance. Wi

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