Re: [R] Help writing basic loop
You did ask for a loop, but if you are willing to consider sapply(), the
result you want can be obtained with a single (admittedly long) command:
slope-sapply(1:100, function(x) lm(c(rnorm(1, mean=.01, sd=.001),
rnorm(1, mean=.1, sd=.01))~c(10,400))$coefficients[2])
head(slope)
c(10, 400) c(10, 400) c(10, 400) c(10, 400) c(10, 400) c(10,
400)
0.0001994346 0.0002118383 0.0002729246 0.0002249865 0.0002323564
0.0002113820
If the c(10, 400) labels are distracting, you can replace them with
consecutive integers:
names(slope)-1:100
head(slope)
12345
6
0.0001994346 0.0002118383 0.0002729246 0.0002249865 0.0002323564
0.0002113820
--
David L Carlson
Associate Professor of Anthropology
Texas AM University
College Station, TX 77843-4352
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of MacQueen, Don
Sent: Friday, September 16, 2011 6:58 PM
To: Luke Miller; beaulieu.j...@epamail.epa.gov
Cc: r-help@r-project.org
Subject: Re: [R] Help writing basic loop
Just a minor aside; I would have done
my.slopes - numeric(100)
Note that:
class(numeric(5))
[1] numeric
-Don
--
Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
925-423-1062
On 9/16/11 12:37 PM, Luke Miller mille...@gmail.com wrote:
Create an output vector to hold your slopes before starting the loop, then
use your index i to place each new slope in the appropriate position in
your
vector.
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
my.slopes = vector(numeric,100) # initialize a numeric vector, length
100, filled with zeros initially
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
my.slopes[i] = slope1 # stick each new slope value into my.slopes[i]
}
You could skip the slope1 - model1$coefficients[2] step and just put the
slope directly into my.slopes[i] as well.
On Fri, Sep 16, 2011 at 3:25 PM, beaulieu.j...@epamail.epa.gov wrote:
Hello,
I would like to write a loop to 1) run 100 linear regressions, and 2)
compile the slopes of all regression into one vector. Sample input data
are:
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
#I have gotten this far with the loop
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
}
How can I compile the slopes from all 100 regressions into one vector?
Thanks,
Jake
[[alternative HTML version deleted]]
__
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and provide commented, minimal, self-contained, reproducible code.
--
___
Luke Miller
Postdoctoral Researcher
Marine Science Center
Northeastern University
Nahant, MA
(781) 581-7370 x318
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and provide commented, minimal, self-contained, reproducible code.
[R] Help writing basic loop
Hello,
I would like to write a loop to 1) run 100 linear regressions, and 2)
compile the slopes of all regression into one vector. Sample input data
are:
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
#I have gotten this far with the loop
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
}
How can I compile the slopes from all 100 regressions into one vector?
Thanks,
Jake
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Help writing basic loop
Create an output vector to hold your slopes before starting the loop, then
use your index i to place each new slope in the appropriate position in your
vector.
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
my.slopes = vector(numeric,100) # initialize a numeric vector, length
100, filled with zeros initially
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
my.slopes[i] = slope1 # stick each new slope value into my.slopes[i]
}
You could skip the slope1 - model1$coefficients[2] step and just put the
slope directly into my.slopes[i] as well.
On Fri, Sep 16, 2011 at 3:25 PM, beaulieu.j...@epamail.epa.gov wrote:
Hello,
I would like to write a loop to 1) run 100 linear regressions, and 2)
compile the slopes of all regression into one vector. Sample input data
are:
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
#I have gotten this far with the loop
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
}
How can I compile the slopes from all 100 regressions into one vector?
Thanks,
Jake
[[alternative HTML version deleted]]
__
R-help@r-project.org 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.
--
___
Luke Miller
Postdoctoral Researcher
Marine Science Center
Northeastern University
Nahant, MA
(781) 581-7370 x318
[[alternative HTML version deleted]]
__
R-help@r-project.org 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] Help writing basic loop
You can also do the regressions in parallel as follows:
x = -25:25
y = 0.05*x^2 + 2* x - 4
y1 = y + rcauchy(51)
y2 = y + rcauchy(51)^2
y3 = y/10 - 5 + rnorm(51)
Y = cbind(y, y1, y2, y3)
m = lm(Y~x)
print(coef(m))
Hope this helps,
Michael
On Fri, Sep 16, 2011 at 3:37 PM, Luke Miller mille...@gmail.com wrote:
Create an output vector to hold your slopes before starting the loop, then
use your index i to place each new slope in the appropriate position in
your
vector.
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
my.slopes = vector(numeric,100) # initialize a numeric vector, length
100, filled with zeros initially
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
my.slopes[i] = slope1 # stick each new slope value into my.slopes[i]
}
You could skip the slope1 - model1$coefficients[2] step and just put the
slope directly into my.slopes[i] as well.
On Fri, Sep 16, 2011 at 3:25 PM, beaulieu.j...@epamail.epa.gov wrote:
Hello,
I would like to write a loop to 1) run 100 linear regressions, and 2)
compile the slopes of all regression into one vector. Sample input data
are:
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
#I have gotten this far with the loop
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
}
How can I compile the slopes from all 100 regressions into one vector?
Thanks,
Jake
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
___
Luke Miller
Postdoctoral Researcher
Marine Science Center
Northeastern University
Nahant, MA
(781) 581-7370 x318
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Help writing basic loop
Just a minor aside; I would have done
my.slopes - numeric(100)
Note that:
class(numeric(5))
[1] numeric
-Don
--
Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
925-423-1062
On 9/16/11 12:37 PM, Luke Miller mille...@gmail.com wrote:
Create an output vector to hold your slopes before starting the loop, then
use your index i to place each new slope in the appropriate position in
your
vector.
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
my.slopes = vector(numeric,100) # initialize a numeric vector, length
100, filled with zeros initially
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
my.slopes[i] = slope1 # stick each new slope value into my.slopes[i]
}
You could skip the slope1 - model1$coefficients[2] step and just put the
slope directly into my.slopes[i] as well.
On Fri, Sep 16, 2011 at 3:25 PM, beaulieu.j...@epamail.epa.gov wrote:
Hello,
I would like to write a loop to 1) run 100 linear regressions, and 2)
compile the slopes of all regression into one vector. Sample input data
are:
y1-rnorm(100, mean=0.01, sd=0.001)
y2-rnorm(100, mean=0.1, sd=0.01)
x-(c(10,400))
#I have gotten this far with the loop
for (i in 1:100) {
#create the linear model for each data set
model1-lm(c(y1[i],y2[i])~x)
slope1-model1$coefficients[2]
}
How can I compile the slopes from all 100 regressions into one vector?
Thanks,
Jake
[[alternative HTML version deleted]]
__
R-help@r-project.org 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.
--
___
Luke Miller
Postdoctoral Researcher
Marine Science Center
Northeastern University
Nahant, MA
(781) 581-7370 x318
[[alternative HTML version deleted]]
__
R-help@r-project.org 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@r-project.org 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 writing for loop
Hi,
I’d like to ask for some help in writing a loop. My situation is the following:
I have a matrix (matrix.A) containing 3 columns and 100 rows. The columns
represent parameter estimates a, b, and c. The rows contain different values
for these parameter estimates. Each row is unique.
I want to insert these parameter estimates into a model (say, y = a + bx +
cx^2) and solve for y given a separate matrix (matrix.B) of x values (where x
has a length of 1500).
I want to solve for y 100 times using each set of the parameter estimates in
matrix.A once.
At present my code looks like this and it only performs the first iteration.
For (i in 1:length(matrix.A)) { y - matrix.A$a[[i]] + matrixA$b[[i]] *
matrix.B$x + matrixA$c[[i]] * matrix.B$x^2)
I have not been able to figure out how to loop through the rows of parameter
estimates in matrix.A. I am new to writing loops, so any assistance would be
much appreciated.
Regards,
Jessica Schedlbauer
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] help writing for loop
Hi,
The great thing about the S language is that it is 'vectorized',
so you can do a lot of matrix manipulations without loops.
Here's a smaller example of what you describe.
matrix A with 3 columns and 10 rows (instead of 100)
matrix B with 3 columns and 15 rows (instead of 1500)
set.seed(123)
mA - matrix(runif(30), ncol = 3)
mA
[,1] [,2] [,3]
[1,] 0.2875775 0.95683335 0.8895393
[2,] 0.7883051 0.45333416 0.6928034
[3,] 0.4089769 0.67757064 0.6405068
[4,] 0.8830174 0.57263340 0.9942698
[5,] 0.9404673 0.10292468 0.6557058
[6,] 0.0455565 0.89982497 0.7085305
[7,] 0.5281055 0.24608773 0.5440660
[8,] 0.8924190 0.04205953 0.5941420
[9,] 0.5514350 0.32792072 0.2891597
[10,] 0.4566147 0.95450365 0.1471136
x - seq(15)
mB - cbind(1, x, x^2)
mB
x
[1,] 1 1 1
[2,] 1 2 4
[3,] 1 3 9
[4,] 1 4 16
[5,] 1 5 25
[6,] 1 6 36
[7,] 1 7 49
[8,] 1 8 64
[9,] 1 9 81
[10,] 1 10 100
[11,] 1 11 121
[12,] 1 12 144
[13,] 1 13 169
[14,] 1 14 196
[15,] 1 15 225
mR - apply(mB, 1, function(x){mA %*% x})
mR
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 2.133950 5.759401 11.163931 18.347540 27.310227 38.05199 50.57284
[2,] 1.934443 4.466187 8.383538 13.686496 20.375061 28.44923 37.90901
[3,] 1.727054 4.326145 8.206250 13.367368 19.809500 27.53265 36.53681
[4,] 2.449921 6.005363 11.549346 19.081867 28.602929 40.11253 53.61067
[5,] 1.699098 3.769140 7.150594 11.843459 17.847736 25.16342 33.79052
[6,] 1.653912 4.679328 9.121806 14.981344 22.257943 30.95160 41.06232
[7,] 1.318259 3.196545 6.162963 10.217513 15.360195 21.59101 28.90995
[8,] 1.528621 3.353106 6.365876 10.566930 15.956267 22.53389 30.29979
[9,] 1.168515 2.363915 4.137635 6.489674 9.420032 12.92871 17.01571
[10,] 1.558232 2.954077 4.644149 6.628448 8.906974 11.47973 14.34671
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 64.87276 80.95176 98.80984 118.44700 139.86324 163.05856 188.03295
[2,] 48.75440 60.98539 74.60199 89.60419 105.99201 123.76542 142.92445
[3,] 46.82198 58.38816 71.23536 85.36358 100.77281 117.46305 135.43430
[4,] 69.09735 86.57257 106.03633 127.48863 150.92947 176.35884 203.77676
[5,] 43.72904 54.97896 67.54029 81.41304 96.59720 113.09277 130.89975
[6,] 52.59011 65.53495 79.89685 95.67582 112.87184 131.48493 151.51508
[7,] 37.31703 46.81224 57.39559 69.06706 81.82667 95.67440 110.61027
[8,] 39.25398 49.39646 60.72722 73.24626 86.95358 101.84919 117.93309
[9,] 21.68102 26.92466 32.74662 39.14689 46.12549 53.68240 61.81763
[10,] 17.50792 20.96335 24.71302 28.75691 33.09502 37.72737 42.65394
[,15]
[1,] 214.78642
[2,] 163.46908
[3,] 154.68657
[4,] 233.18322
[5,] 150.01814
[6,] 172.96229
[7,] 126.63428
[8,] 135.20527
[9,] 70.53119
[10,] 47.87474
so the results matrix mR has one column for each element of x,
and the i-th row element is the solution for
y = a + bx + cx^2
for the i-th row of coefficients in the parameter estimates matrix mA
You can spot check with e.g.
mA[1,] %*% mB[15,]
[,1]
[1,] 214.7864
mA[1,] %*% mB[5,]
[,1]
[1,] 27.31023
mA[1,]
[1] 0.2875775 0.9568333 0.8895393
mB[5,]
x
1 5 25
HTH
Steven McKinney, Ph.D.
Statistician
Molecular Oncology and Breast Cancer Program
British Columbia Cancer Research Centre
email: smckinney +at+ bccrc +dot+ ca
tel: 604-675-8000 x7561
BCCRC
Molecular Oncology
675 West 10th Ave, Floor 4
Vancouver B.C.
V5Z 1L3
Canada
From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] On Behalf Of
Jessica Schedlbauer [jsche...@fiu.edu]
Sent: November 25, 2009 10:43 AM
To: r-help@r-project.org
Subject: [R] help writing for loop
Hi,
I’d like to ask for some help in writing a loop. My situation is the following:
I have a matrix (matrix.A) containing 3 columns and 100 rows. The columns
represent parameter estimates a, b, and c. The rows contain different values
for these parameter estimates. Each row is unique.
I want to insert these parameter estimates into a model (say, y = a + bx +
cx^2) and solve for y given a separate matrix (matrix.B) of x values (where x
has a length of 1500).
I want to solve for y 100 times using each set of the parameter estimates in
matrix.A once.
At present my code looks like this and it only performs the first iteration.
For (i in 1:length(matrix.A)) { y - matrix.A$a[[i]] + matrixA$b[[i]] *
matrix.B$x + matrixA$c[[i]] * matrix.B$x^2)
I have not been able to figure out how to loop through the rows of parameter
estimates in matrix.A. I am new to writing loops, so any assistance would be
much appreciated.
Regards,
Jessica Schedlbauer
__
R-help@r-project.org 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
