Thank you for providing a clarifying example. I think a useful function
for you to get familiar with is the "ave" function. It is kind of like
aggregate except that it works when the operation you want to apply to the
group of elements will returns the same number of elements as were given
to i
Dear Jim,
I don't think my problem is clear the way I put.
I have been trying to manually apply the formula to some rows.
This is what I have done.
I cut and past some rows from 1-7 and save each with a different file as
shown below:
1 8590 12516
2 8641 98143
3 8705 98916
4 8750 89911
5 8685 10
Dear Jim,
I wish also to use the means calculated and apply a certain formula on the
same data frame. In particular, I would like to subtract the means of each
of these seven days from each of the seven days and and divide the outcome
by the same means. If I represent m1 by the means of each seven
On Wed, Nov 28, 2018 at 4:31 AM Jim Lemon wrote:
> Hi Ogbos,
> If we assume that you have a 3 column data frame named oodf, how about:
>
> Dear Jim,
Thank you so much.
The code just made life very easier for me.
best regards
Ogbos
> oodf[,4]<-floor((cumsum(oodf[,1])-1)/28)
> col2means<-by(o
Hi Ogbos,
If we assume that you have a 3 column data frame named oodf, how about:
oodf[,4]<-floor((cumsum(oodf[,1])-1)/28)
col2means<-by(oodf[,2],oodf[,4],mean)
col3means<-by(oodf[,3],oodf[,4],mean)
Jim
On Wed, Nov 28, 2018 at 2:06 PM Ogbos Okike wrote:
>
> Dear List,
> I have three data-column
Dear List,
I have three data-column data. The data is of the form:
1 8590 12516
2 8641 98143
3 8705 98916
4 8750 89911
5 8685 104835
6 8629 121963
7 8676 77655
1 8577 81081
2 8593 83385
3 8642 112164
4 8708 103684
5 8622 83982
6 8593 75944
7 8600 97036
1 8650 104911
2 8730 114098
3 8731 99421
4 871
Of course, this particular example is trivially solvable by hand: x ==y
==p/4 , a square.
Note also that optimization with equality constraints are generally
solvable by the method of Lagrange multipliers for smooth functions and
constraints, so that numerical methods may not be needed for relative
Hi Duncan Murdoch
Thank you for your support.
Best regards,
Nhat Tran
Vào Th 3, 27 thg 11, 2018 vào lúc 23:06 Duncan Murdoch <
murdoch.dun...@gmail.com> đã viết:
> On 27/11/2018 7:53 AM, Thanh Tran wrote:
> > Dear all,
> >
> >
> >
> > I'm trying to plot a surface over the x-y plane. In my data
Hi,
R is quite good at optimization. Here's a basic tutorial:
https://www.is.uni-freiburg.de/resources/computational-economics/5_OptimizationR.pdf
There are a LOT of possibilities:
https://cran.r-project.org/web/views/Optimization.html
Sarah
On Tue, Nov 27, 2018 at 6:19 PM FAIL PEDIA
wrote:
>
Hello, and thanks to anyone who takes the time to read this
I'm trying to learn to properly optimize a function with a constraint using
R. For example, maximize the area of a terrain with a maximum perimeter.
For this example the function would be:
Area <- function(x,y){x*y}
The restriction
Hello R Experts!
Does anyone know of a relatively straightforward way to bootstrap
hypothesis tests for proportion in R?
Thanks in advance!
Janh
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Hi,
I had to include
library(reshape2)
to get things working as you use melt(). Explicitly setting the x and y values
in geom_text() is needed since you are providing new data.
zp1 <- zp1 + geom_text(data=test2, x=test2$con, y=test2$Prob, label =
test2$Project, size = 6, color = "white")
I am experiencing issues with trying to label points added to a ggplot via
geom_point. I think an underlying issue is the fact that I already used ggplot
function to create a 5x5 risk matrix "background", but I am not certain. I have
tried multiple solutions online but cannot find one that has a
Thank you for the clarification.
I'll share a function I got tomorrow morning.
Regards
On Tue, 27 Nov 2018, 18:38 Bert Gunter, wrote:
> ... but do note that a nonlinear fit to the raw data will give a(somewhat)
> different result than a linear fit to the transformed data. In the former,
> the e
... but do note that a nonlinear fit to the raw data will give a(somewhat)
different result than a linear fit to the transformed data. In the former,
the errors are additive and in the latter they are multiplicative. Etc.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that pe
Hi,
Please also include R-help in your replies - I can't provide
one-on-one tutorials.
Without knowing where you got your sample code, it's hard to help. But
what are you trying to do?
It doesn't have to be that complicated:
x <- 1:10
y <- c(0.00, 0.00,0.0033,0.0009,0.0025,0.0653,0.1142,0.2872,
On 27/11/2018 7:53 AM, Thanh Tran wrote:
Dear all,
I'm trying to plot a surface over the x-y plane. In my data, the response
is KIC, and 4 factors are AC, AV, T, and Temp. I want to have response
surface of KIC with two factors, i.e., AC and AV. A typical second-degree
response modeling is as
Dear all,
I'm trying to plot a surface over the x-y plane. In my data, the response
is KIC, and 4 factors are AC, AV, T, and Temp. I want to have response
surface of KIC with two factors, i.e., AC and AV. A typical second-degree
response modeling is as follows:
> data<-read.csv("2.csv", heade
Hi,
Using rseek.org to search for exponential regression turns up lots of
information, as does using Google.
Which tutorials have you worked thru already, and what else are you looking
for?
Sarah
On Tue, Nov 27, 2018 at 5:44 AM Tolulope Adeagbo
wrote:
> Good day,
> Please i nee useful materia
Good day,
Please i nee useful materials to understand how to use R for exponential
regression.
Many thanks.
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