Automating R for Hypothesis Testing

Wed, May 9, 2012 7:55 AM

Hello,

Yes, it does help. Now we can see your data and what you're doing.
What follows is a suggestion on what you could do, not full solution.
(You forgot to say what X1 is, but I don't think it's important to
understand the suggestion.)
(If I'm wrong, say something.)


milwaukeephos <- read.csv("milwaukeephos.csv", header=TRUE,
stringsAsFactors=FALSE)
# list of data.frames, one per month
ls1 <- split(milwaukeephos, milwaukeephos$month)

#--------- if you want to keep the models, not needed if you don't.
#          (yoy probably don't)
modelH <- vector("list", 12)
modelHa <- vector("list", 12)
modelH2 <- vector("list", 12)
modelH2a <- vector("list", 12)
#--------- values to record, these are needed, create them beforehand.
chi_fm <- numeric(12)
chi_fms <- numeric(12)
#
seq_months <- c(1:12, 1) # wrap months around.
for(i in 1:12){
	month_this <- seq_months[i]
	month_next <- seq_months[i + 1]

	lload <- c(ls1[[month_this]]$load_kg, ls1[[month_next]]$load_kg)
	lflow <- c(ls1[[month_this]]$flow, ls1[[month_next]]$flow)
	modelH[[i]] <- lm(lload ~ lflow)
	# If you don't want to keep the models, use modelH only
	# ( without [[i]] )
	# and do the same with X1

	# rest of your code for first test goes here
	chi_fm[i] <- bfm %*% var_fm %*% (bunres_fm - bres_fm)

	# and the same for the second test
	chi_fms[i] <- ...etc...
}


Hope this helps,

Rui Barradas


meredith wrote

dput:  http://r.789695.n4.nabble.com/file/n4620188/milwaukeephos.csv
milwaukeephos.csv 

# Feb-march

modelH_febmarch<-lm(llfeb_march~lffeb_march)
modelHa_febmarch<-lm(llfeb_march~X1feb_mar+lffeb_march)
anova(modelHa_febmarch)
coefficients(modelH_febmarch)

(Intercept) lffeb_march 
  -2.429890    1.172821

coefficients(modelHa_febmarch)

(Intercept)   X1feb_mar lffeb_march 
 -2.8957776  -0.5272793   1.3016303

bres_fm<-matrix(c(-2.429890,0,1.172821),nrow=3)
bunres_fm<-matrix(c(-2.8957776,-0.5272793,1.3016303),nrow=3)
bfm<-t(bunres_fm-bres_fm)
fmvect<-seq(1,1,length=34)
X1a_febmar<-seq(0,0,length=9) # dummy variable step 1
X1b_febmar<-seq(1,1,length=25) # dummy variable step 2
X1feb_mar<-c(X1a_febmar,X1b_febmar) #dummy variable creation

# Test Stat Equation for Chisq

fmxx<-cbind(fmvect,X1feb_mar,lffeb_march)
tfmx<-t(fmxx)
xcom_fm<-(tfmx %*% fmxx)
xinv_fm<-ginv(xcom_fm)
var_fm<-xinv_fm*0.307
chi_fm<-bfm %*% var_fm %*% (bunres_fm-bres_fm)
chi_fm # chisq value for recording

if less than CV move onto to slope modification

modelH2_febmarch<-lm(llfeb_march~X3feb_march)
modelH2a_febmarch<-lm(llfeb_march~X3feb_march+X4feb_march)
anova(modelH2a_febmarch)
coefficients(modelH2_febmarch) # get coefficients to make beta vectors
for test

(Intercept) X3feb_march 
   5.342130    1.172821

coefficients(modelH2a_febmarch)

(Intercept) X3feb_march X4feb_march 
  5.2936263   1.0353752   0.2407557 
# Test Stat

bsres_fm<-matrix(c(5.342130,1.172821,0),nrow=3)
bsunres_fm<-matrix(c(5.2936263,1.0353752,0.2407557),nrow=3)
bsfm<-t(bsunres_fm-bsres_fm)
#X matrix
fmxs<-cbind(fmvect,X3feb_march,X4feb_march)
tfmxs<-t(fmxs)
xcoms_fm<-(tfmxs %*% fmxs)
xinvs_fm<-ginv(xcoms_fm)
var_fms<-xinvs_fm*0.341
chi_fms<-bsfm %*% var_fms %*% (bsunres_fm-bsres_fm)
chi_fms

# Record Chisq value

Does this help?
Here lffeb_march is the combination of Feb and March log flows
and llfeb_march is the combination of Feb and March log loads
X3: lffeb_march-mean(feb_march)
X4: X1*X3

Thanks

Rui Barradas wrote

Hello,

I'm not at all sure if I understand your problem. Does this describe it?


test first model for months 1 and 2
if test statistic less than critical value{
	test second model for months 1 and 2
	print results of the first and second tests? just one of them?
}
move on to months 2 and 3
etc, until months 12 and 1


Please post example data using dput(dataset).
Just copy it's output and paste it in your post.

And example code, what you're already doing.
(Possibly simplified)

Rui Barradas


meredith wrote

R Users-
  I have been trying to automate a manual code that I have developed for
calling in a .csv file, isolating certain rows and columns that
correspond to specified months:
something to the effect
i=name.csv
N=length(i$month)
iphos1=0
iphos2=0
isphos3=0
for i=1,N
 if month=1
    iphos1=iphos+1
    iphos1(iphos1)=i

an so on to call out the months into there own arrays (unless there is a
way I can wrap it into the next automation)

Next: I would like to run a simple linear regression combining each of
the months 1 by 1:
for instance I want to run a regression on a combined model from months
1 and 2 and a dummy model for 1 and 2, compare them using a Chi-sq
distribution, if Chi-sq is less than the Critical value, we accept and
go on to test another set of models with both 1 and 2. If it rejects,
then we proceed to months 2 and 3.  If we move on to the second set on
months 1 and 2, and the critical value is accepted, I want to print an
accept or reject and move on to months 2 and 3, until finally comparing
months 12-1 at the end.
Is there a way to loop or automate this in R?

Thanks
Meredith

Rui Barradas wrote

Hello,

I'm not at all sure if I understand your problem. Does this describe it?


test first model for months 1 and 2
if test statistic less than critical value{
	test second model for months 1 and 2
	print results of the first and second tests? just one of them?
}
move on to months 2 and 3
etc, until months 12 and 1


Please post example data using dput(dataset).
Just copy it's output and paste it in your post.

And example code, what you're already doing.
(Possibly simplified)

Rui Barradas


meredith wrote

R Users-
  I have been trying to automate a manual code that I have developed for
calling in a .csv file, isolating certain rows and columns that
correspond to specified months:
something to the effect
i=name.csv
N=length(i$month)
iphos1=0
iphos2=0
isphos3=0
for i=1,N
 if month=1
    iphos1=iphos+1
    iphos1(iphos1)=i

an so on to call out the months into there own arrays (unless there is a
way I can wrap it into the next automation)

Next: I would like to run a simple linear regression combining each of
the months 1 by 1:
for instance I want to run a regression on a combined model from months
1 and 2 and a dummy model for 1 and 2, compare them using a Chi-sq
distribution, if Chi-sq is less than the Critical value, we accept and
go on to test another set of models with both 1 and 2. If it rejects,
then we proceed to months 2 and 3.  If we move on to the second set on
months 1 and 2, and the critical value is accepted, I want to print an
accept or reject and move on to months 2 and 3, until finally comparing
months 12-1 at the end.
Is there a way to loop or automate this in R?

Thanks
Meredith

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Automating R for Hypothesis Testing

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