# data transformation

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## data transformation

 Dear group, My question, perhaps is more of a statistical question using R I have a data matrix ( 400 x 400 normally distributed) with data points ranging from -1 to +1.. For certain clustering algorithms, I suspect the tight data range is not helping resolving the clusters. Is there a way to transform the data something similar to logit, where I dont lose normality of the data and yet I can better expand the data ranges. Thanks Adrian ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: data transformation

 I apologize,  I forgot to mention another key operation. in my matrix -1 to <0 has a different meaning while values between >0 to 1 has a different set of meaning.  So If I do logit transformation some of the positives becomes negative (values < 0.5 etc.). In such case, the resulting transformed matrix is incorrect. I want to transform numbers ranging from -1 to <0   and numbers between >0 and 1 independently. Thanks ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: data transformation

 I don't think you have given us enough information. For example, is the 500x500 matrix a distance matrix or does it represent 500 columns of information about 500 rows of observations? If a distance matrix, how is distance being measured? You clarification suggests it may be a distance matrix of correlation coefficients? If distance has different meanings between -1 and 0 and 0 and +1, getting interpretable results from cluster analysis will be difficult, but it is not clear what you mean by that. ------------------------------------------------- David L. Carlson Department of Anthropology Texas A&M University -----Original Message----- From: R-help [mailto:[hidden email]] On Behalf Of Adrian Johnson Sent: Sunday, January 20, 2019 8:02 AM To: r-help <[hidden email]> Subject: [R] data transformation Dear group, My question, perhaps is more of a statistical question using R I have a data matrix ( 400 x 400 normally distributed) with data points ranging from -1 to +1.. For certain clustering algorithms, I suspect the tight data range is not helping resolving the clusters. Is there a way to transform the data something similar to logit, where I dont lose normality of the data and yet I can better expand the data ranges. Thanks Adrian ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained -----Original Message----- From: R-help [mailto:[hidden email]] On Behalf Of Adrian Johnson Sent: Sunday, January 20, 2019 10:08 AM To: r-help <[hidden email]> Subject: Re: [R] data transformation I apologize,  I forgot to mention another key operation. in my matrix -1 to <0 has a different meaning while values between >0 to 1 has a different set of meaning.  So If I do logit transformation some of the positives becomes negative (values < 0.5 etc.). In such case, the resulting transformed matrix is incorrect. I want to transform numbers ranging from -1 to <0   and numbers between >0 and 1 independently. Thanks ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.