Explain kleiner hartigan trees, Advanced Statistics

Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal branches and the terminal branches have lengths which rely on the sums of the terminal branches they support. One significant feature of these trees which distinguishes them from most other compound characters, for instance, Chernoff's faces, is that an attempt is made to get rid of the arbitrariness of assignment of the variables by performing the agglomerative hierarchical cluster analysis of variables and using the resultant dendrogram as the foundation tree.
1882_Kleiner Hartigan trees.png 

Posted Date: 7/30/2012 1:29:41 AM | Location : United States







Related Discussions:- Explain kleiner hartigan trees, Assignment Help, Ask Question on Explain kleiner hartigan trees, Get Answer, Expert's Help, Explain kleiner hartigan trees Discussions

Write discussion on Explain kleiner hartigan trees
Your posts are moderated
Related Questions
The Null Hypothesis - H0: β0 = 0, H0: β 1 = 0, H0: β 2 = 0, Β i = 0 The Alternative Hypothesis - H1: β0 ≠ 0, H0: β 1 ≠ 0, H0: β 2 ≠ 0, Β i ≠ 0      i =0, 1, 2, 3

Cointegration : The vector of not motionless time sequence is said to be cointegrated if the linear combination of the individual series is stationary. Facilitates suitable testing

what is operational gaining

The scatter plot of SRES1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plot show that th

I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try

Coefficient of concordance : The coef?cient is taken in use to assess the agreement among m raters ranking n individuals according to some of the speci?c characteristic. Which can

Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible

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

Graduation is the term is employed most often in the application of the actuarial statistics to denote procedures by which the set or group of observed probabilities is adjusted t

when there is tie in sequencing then what we do