[R] A smal fitting problem...
Dear R-helpers, I'm for sure not familiar with R, but it seem like a nice sofware tool, so I've decided to try using it. Here is my problem I just can't figure out: I'd like to do least square fit of a straight horizontal (a = 0) line y = ax + b through some data points x = (3,4,5,6,7,8) y = (0.62, 0.99, 0.83, 0.69, 0.76, 0.82) How would i find b? All the best, Ked [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] A smal fitting problem...
If you really want to fit a horizontal line then the best estimate (meaning least squares) for b is mean(y), regardless of the actual x values, which becomes clear if you look at your design matrix / regressor matrix . In general least squares regression could be done with lsfit(). In your case the design matrix (X matrix) is a simple vector of ones. Kåre Edvardsen schrieb: Dear R-helpers, I'm for sure not familiar with R, but it seem like a nice sofware tool, so I've decided to try using it. Here is my problem I just can't figure out: I'd like to do least square fit of a straight horizontal (a = 0) line y = ax + b through some data points x = (3,4,5,6,7,8) y = (0.62, 0.99, 0.83, 0.69, 0.76, 0.82) How would i find b? All the best, Ked [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] A smal fitting problem...
b = mean(y) On 08/12/06, Kåre Edvardsen [EMAIL PROTECTED] wrote: Dear R-helpers, I'm for sure not familiar with R, but it seem like a nice sofware tool, so I've decided to try using it. Here is my problem I just can't figure out: I'd like to do least square fit of a straight horizontal (a = 0) line y = ax + b through some data points x = (3,4,5,6,7,8) y = (0.62, 0.99, 0.83, 0.69, 0.76, 0.82) How would i find b? All the best, Ked [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- = David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] A smal fitting problem...
On Dec 8, 2006, at 7:42 AM, David Barron wrote: b = mean(y) On 08/12/06, Kåre Edvardsen [EMAIL PROTECTED] wrote: Dear R-helpers, I'm for sure not familiar with R, but it seem like a nice sofware tool, so I've decided to try using it. Here is my problem I just can't figure out: I'd like to do least square fit of a straight horizontal (a = 0) line y = ax + b through some data points x = (3,4,5,6,7,8) y = (0.62, 0.99, 0.83, 0.69, 0.76, 0.82) How would i find b? And in the context of linear models: x - 3:8 y - c(0.62, 0.99, 0.83, 0.69, 0.76, 0.82) lm(y ~ 1) _ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400Charlottesville, VA 22904-4400 Parcels:Room 102Gilmer Hall McCormick RoadCharlottesville, VA 22903 Office:B011+1-434-982-4729 Lab:B019+1-434-982-4751 Fax:+1-434-982-4766 WWW:http://www.people.virginia.edu/~mk9y/ __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.