This is a bit of a shot in the dark since I haven't used randomForest
in several years, but I seem to recall that running randomForest
through the formula interface was asking for trouble... Try not using
the formula interface and specify the x, y, xtest arguments directly.
Peter
On Fri, May 26,
I am trying to do classification with Randomforest() . the class variable
is nominal.
But I get this error
model1 <-randomForest(Cath~.,data=trainrf)
Error in y - ymean : non-numeric argument to binary operator
In addition: There were 26 warnings (use warnings() to see them)
> model1
Error: objec
Hi Michael,
Try not to post twice - this is really more of a general R question. To
answer the question, however, turn each element of your resultlist into an
xts (or zoo) object so that you have a list of xts objects (called xtsList
for example.) Then call do.call("merge", xtsList). Also, yo
I'm not sure how to ask this with the proper terminology, but here goes:
The BDH() function in RBLPAPI returns, for a list of symbols (e.g., 'SPX
Index','RIY Index','IBM Equity') a list of closing prices. The problem is that
the result is not a matrix or a dataframe, but a list.
So, if I run th
Hi David
thanks a lot for your suggestion. I followed the suggestion of Sarah (the
first on the thread) and solved my problem
I will keep into account you suggestion anyway
Mario
On Fri, May 26, 2017 at 4:51 PM, David L Carlson wrote:
> How about?
>
> Trade <- xtabs(FLOW ~ iso_o + iso_d + year,
Thanks a lot for your suggestion. I followed the suggestion of Sarah (the
first on the thread) and solved my problem
I will keep into account you suggestion anyway
Mario
On Fri, May 26, 2017 at 3:28 PM, S Ellison wrote:
> > -Original Message-
> > From: A M > Lavezzi
> >
> > I have data
Hi Duncan
thanks a lot for your suggestion. I followed the suggestion of Sarah (the
first on the thread) and solved my problem
I will keep into account you suggestion anyway
Mario
On Fri, May 26, 2017 at 2:20 PM, Duncan Murdoch
wrote:
> On 26/05/2017 7:46 AM, A M Lavezzi wrote:
>
>> Dear R-User
Hi Ulrik
thanks a lot for your suggestion. I followed the suggestion of Sarah (the
first on the thread) and solved my problem
I will keep into account you suggestion anyway
Mario
On Fri, May 26, 2017 at 2:17 PM, Ulrik Stervbo
wrote:
> Hi Mario,
>
> does acast from the reshape2 package help?
>
>
Dear Sarah
thank you very much. I used "crosstab" and it worked,
xxx<-crosstab(dataTrade$iso_o,dataTrade$iso_d,dataTrade$FLOW,type="sum",na.rm=TRUE)
All the best
Mario
On Fri, May 26, 2017 at 2:15 PM, Sarah Goslee
wrote:
> There are various ways to do this. It shouldn't take forever as a loop,
Hello,
I would like to perform a sensitivity analysis using a Latin Hypercube
Sampling (LHS).
Among the input parameters in the model, I have a parameter �dispersal
distance� which is defined according to an exponential probability distribution.
In the model, the user thus sets a default prob
How about?
Trade <- xtabs(FLOW ~ iso_o + iso_d + year, dta)
Gives you a 3d table with FLOW as the cell entry. Then
apply(Trade, 1:2, sum, na.rm=TRUE)
Gives you a 2d table with the total flow
David L. Carlson
Department of Anthropology
Texas A&M University
-Original Message-
From: R-h
> -Original Message-
> From: A M > Lavezzi
>
> I have data on bilateral trade flows among countries in the following form:
>
> iso_o iso_d year FLOW
> 1 ABW AFG 1985 NA
> 2 ABW AFG 1986 NA
> 3 ABW AFG 1987 NA
> 4 ABW AFG 1988 NA
> 5 ABW AFG 1989 NA
> 6
On 26/05/2017 7:46 AM, A M Lavezzi wrote:
Dear R-Users
I have data on bilateral trade flows among countries in the following form:
head(dataTrade)
iso_o iso_d year FLOW
1 ABW AFG 1985 NA
2 ABW AFG 1986 NA
3 ABW AFG 1987 NA
4 ABW AFG 1988 NA
5 ABW AFG 1989
Hi Mario,
does acast from the reshape2 package help?
dfa<- data.frame(iso_o = letters[c(1, 1:4)], iso_d = letters[6:10], year =
c(1985, 1985, 1986, 1987, 1988), flow = c(1,2,3,4, NA))
reshape2::acast(dfa, iso_o ~ iso_d, fun.aggregate = sum, value.var = "flow")
HTH
Ulrik
On Fri, 26 May 2017 at 1
There are various ways to do this. It shouldn't take forever as a loop,
with only 215 entries.
I find crosstab() from the ecodist package helpful. The current version is
on GitHub, but not yet CRAN (soon!).
Sarah
On Fri, May 26, 2017 at 7:47 AM A M Lavezzi wrote:
> Dear R-Users
>
> I have data
Dear R-Users
I have data on bilateral trade flows among countries in the following form:
> head(dataTrade)
iso_o iso_d year FLOW
1 ABW AFG 1985 NA
2 ABW AFG 1986 NA
3 ABW AFG 1987 NA
4 ABW AFG 1988 NA
5 ABW AFG 1989 NA
6 ABW AFG 1990 NA
where:
iso_o: co
It is correct and will produce a data.frame. But I guess the result is not
what you intend since the resulting data.frame nothing but NA and Samples
in the diagonal:
df1 <- data.frame(x = letters[1:5], y = letters[6:10])
reshape2::dcast(df1, x ~ y)
You are missing values somewhere. If you want al
Dear all, I would like to double-check with you please the use of "acast"
or "dcast" function from "reshape2"package.
I am starting with a data frame Y of GENES and SAMPLES,eg :
Cancer_Gene Sample
1ABL2 WT_10T
2ABL2 WT_6T
3 ADGRA2 HB_8R
4AFF4 EWS_13R
and I
> On 25 May 2017, at 20:35, Elahe chalabi via R-help
> wrote:
>
> Thanks for your reply Bert. But the question on how to plot MDS on predicted
> data I guess belong to here!
Actually, You have 2 questions in conflict.
1- how can I plot MDS on predicted data?
2- Is MDS plot a way to find out
Thanks for your reply Bert. But the question on how to plot MDS on predicted
data I guess belong to here!
On Thursday, May 25, 2017 9:43 AM, Bert Gunter wrote:
Elahe:
On Thu, May 25, 2017 at 8:15 AM, Elahe chalabi via R-help
wrote:
> Hi all,
> I have applied Random Forest on my data and
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