this is what I did to perform a regression between two bricks (each brick
represent a time series):
r - raster(brick1)
for (i in 1:ncell(r)) {
r[i] = lm(as.ts(cellValues(brick1, i)) ~ as.ts(cellValues(brick2,
i)))$coefficients[2]
}
The result will be a slope raster, but it really takes a lot
that's cool, I'm also interested in a similar problem but just with one
brick ending up with a slope raster as the output. It may be possible with
stackApply(). have a look. or maybe robert will chime in
On Fri, Nov 26, 2010 at 1:35 PM, Martin martin_bra...@gmx.net wrote:
this is what I did
mosherste...@gmail.com
Subject: Re: [R-sig-Geo] gridded time series analysis
To: Martin martin_bra...@gmx.net
Cc: r-sig-geo@stat.math.ethz.ch
Date: Friday, 26 November, 2010, 23:33
that's cool, I'm also interested in a similar problem but just with one
brick ending up with a slope raster
bricks have 12 layers)
br3 - stack(brick1, brick2)
lmS - function(x) lm(x[1:12] ~ x[13:24)$coefficients[2]
r - calc(br3, lmS)
Jacob.
--- On Fri, 26/11/10, steven mosher mosherste...@gmail.com wrote:
From: steven mosher mosherste...@gmail.com
Subject: Re: [R-sig-Geo] gridded time series
)
lmS - function(x) lm(x[1:12] ~ x[13:24)$coefficients[2]
r - calc(br3, lmS)
Jacob.
--- On Fri, 26/11/10, steven mosher mosherste...@gmail.com wrote:
From: steven mosher mosherste...@gmail.com
Subject: Re: [R-sig-Geo] gridded time series analysis
To: Martin martin_bra...@gmx.net
Cc: r-sig-geo
Dear Members,
I have two variables on a 507 x 356 grid and each grid cell has a time
series of length 120. Is it possible to perform a time series analysis on
the entire grid all at the same time, with the ultimate goal of doing linear
regressions for each grid point for the 2 variables? Are
