search for: jinsong_zh

Displaying 5 results from an estimated 5 matches for "jinsong_zh".

2004 Aug 03
4
How to select a whole column? Thanks!
...0 0 -0.009 -0.012 -0.015 -0.018 I mean how to select the first four columns. Thank you very much for your consideration on this matter. Best wishes, Jinsong ===== (Mr.) Jinsong Zhao Ph.D. Candidate School of the Environment Nanjing University 22 Hankou Road, Nanjing 210093 P.R. China E-mail: jinsong_zh at yahoo.com
2004 Feb 04
1
center or scale before analyzing using pls.pcr
...be scaled. If the dependent variable is scaled, how I give a prediction to the real data? I appreciate for any suggestions and comments. Best regards, Jinsong ===== (Mr.) Jinsong Zhao Ph.D. Candidate School of the Environment Nanjing University 22 Hankou Road, Nanjing 210093 P.R. China E-mail: jinsong_zh at yahoo.com
2004 Aug 04
1
What's ``impres''?
...cat("blah blah blah \n") Would someone here like to tell me what's the counterpart in R to impres in S+? Thanks in advance! Best wishes, Jinsong ===== (Mr.) Jinsong Zhao Ph.D. Candidate School of the Environment Nanjing University 22 Hankou Road, Nanjing 210093 P.R. China E-mail: jinsong_zh at yahoo.com
2004 Feb 01
5
Stepwise regression and PLS
Dear all, I am a newcomer to R. I intend to using R to do stepwise regression and PLS with a data set (a 55x20 matrix, with one dependent and 19 independent variable). Based on the same data set, I have done the same work using SPSS and SAS. However, there is much difference between the results obtained by R and SPSS or SAS. In the case of stepwise, SPSS gave out a model with 4 independent
2004 Feb 06
1
problem to get coefficient from lm()
Dear all, The following is a example that I run and hope to get a linear model. However, I find the lm() can not give correct coefficients for the linear model. I hope it's just my own mistake. Please help. TIA. Regards, Jinsong > x [1] 3.760216 3.997288 3.208872 3.985417 3.265704 3.497505 2.923540 3.193937 [9] 3.102787 3.419574 3.169374 2.928510 3.153821 3.100385 3.768770 3.610583