Emma Jones writes:
> My current data structure consists of a .csv
> file read into R containing 15 columns (a charcoal dilution series going
>>From 100% to 0%) and 1050 rows of absorbance data from 400 nm to 2500 nm at
> 2 nm interval. I think I need to transpose the data such that the specific
I am having a similar problem understanding the data structure of the
"yarn" dataset described in the "[R] data structure for plsr" posts. I have
spectroscopic data I'd like to run through a PLSR and have read the
tutorial series, but still do not understand the data for
Hi, Jim.
Actually you need to have ad "data.frame" object of define X and Y variables
in it.
DATA$X must contain all data for X varibales (DATA$NIR in example)
DATA$Y response variable(s) for your X matrix data: (DATA$density in example)
For example you have X variables in matrix and one Y varia
From: jim holtman [mailto:[EMAIL PROTECTED]
Sent: Tuesday, October 16, 2007 11:13 AM
To: Bricklemyer, Ross S
Cc: [EMAIL PROTECTED]
Subject: Re: [R] data structure for plsr
try:
str(yarn)
to see what the structure is.
On 10/16/07, Bricklemyer, Ross S <[EMAIL PROTECTED]> wrote:
> All,
try:
str(yarn)
to see what the structure is.
On 10/16/07, Bricklemyer, Ross S <[EMAIL PROTECTED]> wrote:
> All,
>
> I am working with NIR spectral data and it was great to find that the example
> in ?plsr also used spectral data. Unfortunately, I am having difficulty
> figuring out how the "y
All,
I am working with NIR spectral data and it was great to find that the example
in ?plsr also used spectral data. Unfortunately, I am having difficulty
figuring out how the "yarn" dataset is structured to allow for the plsr model
to read:
library(pls)
data(yard)
yarn.oscorespls <- mvr(den
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