Displaying 7 results from an estimated 7 matches for "grenke".
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grenie
2011 Jan 22
4
two apparent anomalies
(1)
> a = c("a","b")
> mode(a)
[1] "character"
> b = c(1,2)
> mode(b)
[1] "numeric"
> c = data.frame(a,b)
> mode(c$a)
[1] "numeric"
(2)
> a = c("a","a","b","b","c")
> levels(as.factor(a))
[1] "a" "b" "c"
> levels(as.factor(a[1:3]))
[1]
2011 Jan 20
2
reading in time series
This is causing me great consternation, and I've spent too much time
floundering around on it.
My data is in the form of columns in Excel, with the first column being in
m/dd/yyyy hh:mm format. The spreadsheet is complicated (headers, merged
cells, lines w/o data); so I've tried various ways of exporting the data
into a text file for the R processing - CSV, spaced, etc. For example:
2011 Jan 20
1
Scale of 2nd y-axis
Dear list,
My query follows on from a question I posted a few days ago. I have the following 2 sets of data:
wetMeans[1] 9.904762[2] 6.344828[3] 6.346154[4] 6.855769[5] 9.074324[6] 9.953988[7] 13.482966[8] 14.546053[9] 10.841584[10] 9.752033[11] 6.739336[12] 8.955056burnMeans[1] 0.06214286[2] 0.05396552[3] 0.04096154[4] 0.05302885[5] 0.05831081[6] 0.07392638[7] 0.29969940[8] 0.25596217[9]
2011 Jan 21
3
complex transformation of data
Dear [R] people
Could you please help with following data transformation.
Any suggestions, hints, references and even guessing on performing any
of the following steps are highly appreciated. Those transformations are
crucial for my work.
(n_, _n, j_, k_ signify numbers)
SOURCE DATA:
id cycle1 cycle2 cycle3 ? cycle_n
1 c c c c
1 m m m m
1 f f f f
2 m m m NA
2 f f f NA
2 c c c NA
3 a a
2011 Jan 21
3
data and parameters
(1) I have a master data frame that reads
ClientID |date |value
(2) I also have a control data frame that reads
Client ID| Min date| Max date| control parameters
The control data set may not have all client IDs .
I want to use the control data frame on the master data frame to
remove client IDS that don't exist in the control data set and for
those that do, remove dates outside the
2011 Jan 20
6
Identify duplicate numbers and to increase a value
Hi everybody.
I want to identify duplicate numbers and to increase a value of 0.01 for each time that it is duplicated.
Example:
x=c(1,2,3,5,6,2,8,9,2,2)
I want to do this:
1
2 + 0.01
3
5
6
2 + 0.02
8
9
2 + 0.03
2 + 0.04
I am trying to get something like this:
1
2.01
3
5
6
2.02
8
9
2.03
2.04
Actually I just know the way to identify the duplicated numbers
rbind(x, duplicated(x) |
2011 Jan 22
0
how to call BayesX in R to see the graph
...k Harrell)
20. Re: Regression Testing (Mojo)
21. Re: Regression Testing (Achim Zeileis)
22. Re: User input in R program (Matt Shotwell)
23. Re: User input in R program (D Kelly O'Day)
24. Re: complex transformation of data (ONKELINX, Thierry)
25. Re: complex transformation of data (Moritz Grenke)
26. Re: User input in R program (Mauricio Zambrano)
27. Error in ANOVA for model comparison (Rosario Garcia Gil)
28. HHT-methodology (Torbj?rn Lorentzen)
29. Help for lattice. par(new=TRUE) (Fabrice Tourre)
30. Re: Regression Testing (Mojo)
31. Re: Regression Testing (Achim Zeileis)
32. Re:...