Redundancy analysis, Applied Statistics

In reduced rank regression (RRR), the dependent variables are first submitted to a PCA and the scores of the units are then used as dependent variables in a series of stafldard MLR's where the original independent variables are used as predictors (a procedure akin to an inverse principal component regression).

Posted Date: 4/4/2013 3:30:10 AM | Location : United States







Related Discussions:- Redundancy analysis, Assignment Help, Ask Question on Redundancy analysis, Get Answer, Expert's Help, Redundancy analysis Discussions

Write discussion on Redundancy analysis
Your posts are moderated
Related Questions
The data in the data frame asset are from Myers (1990), \Classical and Modern Regression with Applications (Second Edition)," Duxbury. The response y here is rm return on assets f

If the test is two-tailed, H1:  μ ≠  μ 0  then the test is called two-tailed test and in such a case the critical region lies in both the right and left tails of the sampling distr

A researcher hypothesized that the pulse rates of long-distance athletes differ from those of other athletes. He believed that the runners’ pulses would be slower. He obtained a ra

what is the aim of statistics?

You are given the differential equation dy/dx = y' = f(x, y) with initial condition y(0 ) 1 = . The following numerical method is also given: where  f n = f( x n , y n )

Geometric Mean is defined as the n th root of the product of numbers to be averaged. The geometric mean of numbers X 1 , X 2 , X 3 .....X n is given as

Accident proneness  A personal psychological issue which affects the individual's probability of suffering the accident. The concept has been studied statistically under the num

PROPERTIES   1. The value of standard deviation remains the same if, in a series each of the observation is increased or decreased by a constant quantity. In statistical lan

Your company operates a machine shop, and, having heard you had experience in statistics and design of experiments, consulted you for your opinion on an experiment they want to run

The 4 assumptions of regression: 1.       Variables are normally distributed 2.       Linear relationship between the independent and dependent variables 3.       Homosced