Probably not the most elegant, but a workable solution. Assume you have a
matrix x of dimensions 10 x 10. Assume further you want to calculate the
mean for each successive block of two columns. One way to do this is to
create a matrix that indicates the column numbers from/to which to apply the
Use the tapply() function as in tapply(b,m,sum)
HTH,
Daniel
mousy0815 wrote:
...
I wanted to get the sum of the probability at all the values of b (ie.
Probability(10, 0.1, 1, 1, 4, 5) + Probability(10, 0.1, 1, 2, 4, 5)... +
Probability(10, 0.1, 1, 9, 4, 5). For that I can just use
The problem arises in the computation of U where (-dummy+1) turns negative
(the eighth and higher index values of dummy). You raise a negative number
to a non-integer power, for example, (-pi)^exp(1), which fails because you
would not be able to tell, which sign the resulting number should have.
Thanks, Uwe, for sending me this the second time. I send my responses through
nabble. So #1 does not seem to be an option; #2 I sometimes forget.
Regards,
Daniel
Uwe Ligges-3 wrote:
On 02.07.2011 20:51, Daniel Malter wrote:
You can just tell the function to create 1000 random numbers. See
Say you have the string x in a matrix
x-c('a,..gGGtTaac!T','caaGGTT,,.!!@CC')
x-matrix(x)
remove all punctuation:
x1-gsub('[[:punct:]]','',x)
x1
convert all letter to lowercase
x2-gsub('(\\w*)','\\L\\1',x1,perl=T)
x2
now for each row split the string and table it. apply over all rows in the
You can just tell the function to create 1000 random numbers. See ?runif for
the specifics. The arguments are n, min, and max. 'n' is the one you are
looking for.
Da.
--
View this message in context:
http://r.789695.n4.nabble.com/Repeating-a-function-in-R-tp3640508p3640966.html
Sent from the R
If you want to repeat an entire function, use replicate as in
replicate(15,sapply(1,function(x) runif(x)))
Here, sapply(1,function(x) runif(x)) draws on uniformly distributed
variable. replicate(15,...) is the wrapper function that tells to do this 15
times. The benefit here is that you can
Hi all,
I have two numeric variables that form combinations in a matched sample.
Let's say I have five levels of x and y. What I am seeking to create is a
factor variable that ignores the order of x and y, i.e., the factor should
indicate x=1, y=5, as the same factor as x=5, y=1. Obviously, this
You can specify the weights=... argument in the lm() function as vector of
weights, one for each observation. Should that not do what your are trying
to do?
HTH,
Daniel
--
View this message in context:
I think you should write out your model formula and then go over it term by
term to see which term adds what to your understanding of the data. If
necessary, pick up a text about the interpretation of coefficients. For
example, you will find that Reduction is not just the slope for the
condition
For example, you can merge the two data frames and do a direct comparison:
df-merge(x,y,all.x=T,all.y=F)
df
df$Qdf$Threshold_Q
HTH,
Daniel
Ryan Utz-2 wrote:
Hi all,
I have two datasets, one that represents a long-term time series and one
that represents summary data for the time
I am not an expert in this. But try try() :)
hth,
Daniel
Sam Nicol wrote:
Hi R-users,
I'm attempting to fit a number of mixed models, all with the same
structure, across a spatial grid with data points collected at various
time points within each grid cell. I'm trying to use a 'for'
The reason you get NAs is the rank deficiency. It even says that five
coefficients are not defined because of singularities. It is likely the case
that certain categories do not exist in the data. Note that in the example
below y is ALWAYS zero when x is zero. This makes an interaction inestimable
Let us work backward. The pic_onscr() fails because lda_result does not
exist. lda_result does not exist because your lda() fails. Your lda() fails
because Error in lda.default(x, grouping, ...) :
variables 1 3 5 8 10 15 17 20 27 29 34 appear to be constant within
groups This indicates that
I find this sign in the code multiple times: ¨C; I replaced those with *;
there is also a MS-Word flexible hyphenation sign in there somewhere,
probably standing for a minus sign. Other than that, there are a couple of
output calls within loops that do not do anything anyway, but which seem to
be
Hi,
can you put return(models) within the inner braces and report what it
does. That might do the trick, since it should return the 'models' for every
combination of i and j.
HTH,
Daniel
hazzard wrote:
Hi,
I have two datasets, x and y. Simplified x and y denote:
X
Y
A B C A B
To be more accurate and helpful, try this:
fun- function(x,y){
for(i in 1:length(colnames(x))){
for(j in 1:length(colnames(y))){
if(colnames(x)[i]==colnames(y)[j]){
models=list(lm(ts(x[i])~ts(y[j])))
return(models)
You probably want to use the merge() function.
imaginary example for data frames named KS and US, where the common
identifier variable is named ID
merged.data-merge(KS,US,by.x=ID,by.y=ID,all.x=F,all.y=F)
Note that this will retain only observations for which there is a common ID
in both KS and
Hi, that depends on whether you want to get the minimum within each list
element or the global minimum across all list elements. The first is
achieved by using lapply(). The second can be achieved by unlisting the list
(which assumes that all list elements are numeric) and looking for its
minimum.
I do not understand why that would be the case as the only input involving
the relationship of the data is the determinant of the correlation matrix.
For what you suggest to be true, the non-normality of the data would have
to introduce correlation.
If what you are saying is true, we would
Thanks for the clarification. That makes sense.
To summarize, bartlett.test() in the base distribution of R is not the
sphericity test, and it relies on the higher moments of the normal
distribution. The sphericity test can be computed with the formula provided
or the one implemented in the psych
It likely means that your x and y are differently long. That is, affect1 and
adh1scr do not contain the same number of values in that instance. That
precludes them from being plotted against each other. abline and lowess
would fail for the same reason.
x-c(1,2,3)
y-c(2,4)
plot(y~x)
Note what are supposed to be quotation marks around ID in your post are a
circumflex instead. Maybe the problem is that the quotation marks that are
supposed to be around ID are not recognized by your R version. May you do
not use the proper font encoding. Use straight quotation marks or
A function for non-parametric multivariate analysis of variance (should do
univariate, too, I guess) allowing for interactions (as far as I can tell)
is implemented in the anosim() function of the vegan package.
See also:
http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
I am sure there is a more elegant version of doing this. But this works:
x-rnorm(20)
y-matrix(1:5) #number of points to sample
f-function(z){sample(x,z)}
apply(y,1,f)
Just adjust y to your liking.
HTH,
Daniel
alfredo wrote:
Hi All,
I'd like to randomly sample a vector N times, where
This question was just answered yesterday in this post:
http://r.789695.n4.nabble.com/Correlations-by-subgroups-td3599548.html#a3600553
One solution:
x-c(1,1,1,1,1,2,2,2,2,2)
y-rnorm(10)
z-y+rnorm(10)
by(data.frame(y,z),factor(x),cor)
HTH,
Daniel
Mateus Rabello wrote:
Hi,
How can I
The formula for the chi-square value is:
-( (n-1) - (2*p-5)/6 )* log(det(R))
where n is the number of observations, p is the number of variables, and R
is the correlation matrix. The chi square test is then performed on
(p^2-p)/2 degrees of freedom. So you can compute it by hand. Or you can use
I am not sure what you actually want to accomplish. If you try to correlate
numeric/rank data with text data, I have no clue how that could be achieved
(other than with text length, or presence/absence of a comment). If you try
to figure out how you prevent the cor() function to fail when it
:234
Gabor Grothendieck wrote:
On Wed, Jun 15, 2011 at 6:05 PM, Daniel Malter lt;dan...@umd.edugt;
wrote:
There may be two issues here. The first might be that, if I understand
the
Bass model correctly, the formula you are trying to estimate is the
adoption
in a given time period. What you
in nabble, either private msg or
for everyone to see, but not both.
Da.
Uwe Ligges-3 wrote:
On 14.06.2011 22:29, Daniel Malter wrote:
Hi,
pick up any introductory manual of which there are many online. It so
happens that the functions for mean and sd are called mean() and sd(). If
you want
I did not intend to bully you but rather tried to speak narrowly to the core
of the issue. In a sense the point was that the example you used to
illustrate the problem created part of the problem and that in a sensical
dataset you would not obtain nonsensical results. Secondly, my reply talked
to
x-c(1,1,1,1,1,2,2,2,2,2)
y-rnorm(10)
z-y+rnorm(10)
by(data.frame(y,z),factor(x),cor)
hth,
Daniel
jfdawson wrote:
I'm hoping there is a simple answer to this - it seems that there should
be, but I can't figure it out.
I have a matrix/data frame with three variables of interest - V1, V2,
x-'GTTACTGGTACC'
table(strsplit(x,''))
hth,
Daniel
karena wrote:
Hi,
I have a string GGCCCAATCGCAATTCCAATT
What I want to do is to count the percentage of each letter in the string,
what string functions can I use to count the number of each letter
appearing in the string?
There may be two issues here. The first might be that, if I understand the
Bass model correctly, the formula you are trying to estimate is the adoption
in a given time period. What you supply as data, however, is the cumulative
adoption by that time period.
The second issue might be that the
Hi,
pick up any introductory manual of which there are many online. It so
happens that the functions for mean and sd are called mean() and sd(). If
you want to know how to use them type ?mean or ?sd in the R-prompt and hit
enter.
Daniel
--
View this message in context:
Hi,
Why does the second example on ?parcoord help page not help you with that?
?parcoord
ir - rbind(iris3[,,1], iris3[,,2], iris3[,,3])
parcoord(log(ir)[, c(3, 4, 2, 1)], col = 1 + (0:149)%/%50)
If that does not do, feel free to get back.
Daniel
--
View this message in context:
I would argue that your Wilcoxon test is meaningless. For all four datasets,
the first data column has no overlap whatsoever with the second data column.
All Wilcoxon Ws are 0. The BIZARRE behavior may be that the test tries to
interpolate what the p value for W of 0 would be given your sample
Where are you stuck? A question without reproducible code or demonstrating
own effort is much less likely to receive a response.
Best,
Daniel
--
View this message in context:
http://r.789695.n4.nabble.com/how-to-convert-careers-to-social-network-description-tp3597622p3598067.html
Sent from the
I am with Michael. It is almost impossible to figure out what you are trying.
However, I assume, like Michael, that you regress y on x2 and find, say, a
negative effect. But when you regress y on x1 and x2, then you find a
positive effect of x2. The short answer to your question is that in this
Thanks everybody.
--
View this message in context:
http://r.789695.n4.nabble.com/Latent-class-analysis-selection-of-the-number-of-classes-tp3545538p3554357.html
Sent from the R help mailing list archive at Nabble.com.
__
R-help@r-project.org mailing
Hi,
I perform latent class analysis on a matrix of dichotomous variables to
create an indicator of class/category membership for each observation. I
would like to know whether there is a function that selects the best fit in
terms of number of classes/categories.
Currently, I am doing this with
As I (thought I) understood from the sendmailR manual, the package does
currently not support server authentication, or does it?
Daniel
--
View this message in context:
http://r.789695.n4.nabble.com/Email-out-of-R-code-tp3530671p3536512.html
Sent from the R help mailing list archive at
What you should and can do depends on the expectations you have regarding the
correlation structure of the data and is limited by your degrees of freedom.
For example, what is wrong about:
reg-lmer(response~femaleset+treatment+(1|group))
?
This assumes that there are constant group effects on
I do not know. I was not aware and could hardly find any information on
create.post(). From what I have seen at first glance, it seems that
create.post() either opens your standard email program or web browser, which
the python code does not. Instead it needs the R-library interfacing Python.
I
Hi all,
I thought I would post code to send an email out of R. The code uses
Grothendieck and Bellosta's interface package rJython for executing Python
from R. The code itself provides basic email functionality for email servers
requiring authentication. It should be easy to extend it (e.g., for
The loop is correct, you just need to make sure that your result is computed
and stored as the n-th element that is returned by the loop. Pick up any
manual of R, and looping will be explained there. Also, I would recommend
that you draw a random number for every iteration of the loop. Defining
Hi,
this response uses the previous responses with an example:
#Assume you have 100 observations
n=100
#Simulate a time series of prices
error=rnorm(n,0,3)
raw.price=rpois(n,100)
lag.price=c(rpois(1,100),raw.price[1:99])
price=lag.price+error
#Say you want the moving average based on this
#and
If you want perfect equality, split the data in good and bad and sample from
the two samples individually.
On average, however, random sampling from the entire data will reproduce the
proportion of good and bad in the data.
hth,
Daniel
--
View this message in context:
Hi,
I summary() a variable with 409908 numeric observations. The variable is
part of a data.frame. The problem is that the min and max returned by
summary() do not equal the ones returned by min() and max(). Does anybody
know why that is?
min(data$vc)
[1] 15452
max(data$vc)
[1] 316148
Thanks all. No I wasn't aware of the fact that summary is rounding in this
case.
Da.
--
View this message in context:
http://r.789695.n4.nabble.com/Precision-of-summary-when-summarizing-variables-in-a-data-frame-tp3428570p3429022.html
Sent from the R help mailing list archive at Nabble.com.
The header metric mds was actually a leftover because I initially used
cmdscale and did not bother changing it for the example.
Thanks,
Daniel
--
View this message in context:
http://r.789695.n4.nabble.com/Plotting-MDS-multidimensional-scaling-tp3422670p3424135.html
Sent from the R help mailing
Hi, I am working on a dataset in which a number of venture capitalists invest
in a number of firms. What I am creating is an asymmetric matrix M in which
m(ij) is the volume (sum) of coinvestments of VC i with VC j (i.e., how much
has VC i invested in companies that VC j also has investments in).
Hi,
I just encountered what I thought was strange behavior in MDS. However, it
turned out that the mistake was mine. The lesson learned from my mistake is
that one should plot on a square pane when plotting results of an MDS. Not
doing so can be very misleading. Follow the example of an
Check whether x, y, or glm have been redefined. If not, restart R.
D.
--
View this message in context:
http://r.789695.n4.nabble.com/I-think-I-just-broke-R-tp3422737p3422932.html
Sent from the R help mailing list archive at Nabble.com.
__
The ?cut function should work for that. Have you tried?
D.
--
View this message in context:
http://r.789695.n4.nabble.com/Discretizing-data-rows-into-regular-intervals-tp3422921p3422933.html
Sent from the R help mailing list archive at Nabble.com.
__
Sorry, I did not get the question because I read it too sloppily. I hope this
is not homework. You can proceed along this example:
set.seed(32345)
#Value of observation
value=rpois(60,100)
#Day of observation
day=sample(1:1080,50,replace=F)
day=sort(day)
#Assume 3 years
#Assume months have all
Hi, these are pretty basic questions. You might want to pick up an
introductory manual.
Lets assume you have a time stamp that already indicates the hours. Assume
you have 300 observations, each of which falls in one of 24 hours of
observation. You easily get the number of obs in each hour with
Hi, has there been a solution to this issue? I am encountering the same
problem on a Mac with OSX 10.6.4. The problem persists when I try to install
lme4 from the source (see below), and my R version is up to date according
to R's update check.
Thanks for any help,
Daniel
--
Hi, I have a good grasp of grep() and gsub() for finding and extracting
character strings. However, I cannot figure out how to use a search term
that is stored in a variable when the search string is more complex.
#Say I have a string, and want to know whether the last name Jannings is
in the
A beauty. Works a charm. Many many thanks.
Daniel
--
View this message in context:
http://r.789695.n4.nabble.com/grep-with-search-terms-defined-by-a-variable-tp2311294p2311307.html
Sent from the R help mailing list archive at Nabble.com.
__
Hi, take the following example and proceed accordingly.
Name=c(Miller,Miller,Miller,Miller,Smith,Smith,Smith,Smith)
X=rnorm(8)
Year=rep(2000:2003,2)
d=data.frame(Name,X,Year)
#Row indices
rows=1:dim(d)[1]
#Which Name occupies which rows?
#Name would be your file
Atte, note the similarity between what Greg described and a bootstrap. The
difference to a true bootstrap is that in Greg's version you subsample the
population (or in other instances the data). This is known as subsampling
bootstrap and discussed in Politis, Romano, and Wolf (1999).
HTH,
Daniel
Atte, I would not wonder if you got lost and confused by the certainly
interesting methodological discussion that has been going on in this thread.
Since the helpers do not seem to converge/agree, I propose to you to use a
different nonparametric approach: The bootstrap. The important thing
Hi, the way it is asked you are not likely to receive an answer to your
question.
The reasons are:
1. Your question is way to unspecific. What kind of panel data analysis? How
should we know? A package for linear panel data models and packages for
random (mixed) effects models are implemented
as.spam.listw is an unknown function. Is it in a different package?
Daniel
other attached packages:
[1] spdep_0.5-11coda_0.13-5 deldir_0.0-12
maptools_0.7-34 foreign_0.8-38 nlme_3.1-96 MASS_7.3-3
[8] Matrix_0.999375-31 lattice_0.17-26
I was missing the spam library.
I did some testing with m x m matrices (see below). Computing 'a' is the
villain. The computation time for 'a' is exponential in m. For a 100 by 100
matrix, the predicted time is about 20 seconds. Thus, 100,000 runs, would
take about 23 days.
library(igraph)
Works wonderfully. I am very happy that I eventually found this post :)
Daniel.
--
View this message in context:
http://r.789695.n4.nabble.com/rbind-with-different-columns-tp907370p2263588.html
Sent from the R help mailing list archive at Nabble.com.
Hi all, I am sorry if this is a very basic quesion, but I have no experience
with analyzing spatial data and could not find the right function/package
quickly. Any hints would be much appreciated. I have a matrix of spatial
point patterns like the one below and want to find the number of
Hi, thanks much. This works in principle. The corrected code is below:
a - nb2mat(cell2nb(nrow(x),ncol(x),torus=T), style=B)
g - delete.vertices(graph.adjacency(a), which(x!=1)-1)
plot(g)
clusters(g)
the $no argument of the clusters(g) function is the sought after number.
However, the function
Hi, you should be able to do most of your summaries using tapply() or
aggregate().
for your example,
tapply(d$Acc,list(d$Sample),table)
Here tapply takes Acc, splits it by Sample, and then tables Acc (which
returns how many 0s/1s were observed in variable Acc for each stratum of
Sample).
Hi, as pointed out previously, the problem is in using the canned routine
(lm) without including an intercept term. Here is a working, generic example
with commented code.
#Simulate data
x=rnorm(100)
e=rnorm(100)
y=x+e
#Create X matrix with intercept
X=cbind(1,x)
#Projection matrix
You can define a function that does just that: sum the 1s in Acc and divide
by the length of Acc. Then use tapply to apply the function for each
subject.
f=function(x){sum(as.numeric(as.character(x)))/length(x)}
tapply(d$Acc,list(d$S),f)
HTH,
Daniel
--
View this message in context:
these websites seem to have the data. though I have not checked for
completeness. the rsssf in particular is seems to be concerned with
collecting and archiving these kinds of football data:
http://www.rsssf.com/tablesw/worldcup.html
http://wapedia.mobi/en/1930_FIFA_World_Cup_Group_1
hope that
Hi, one approach is document below. The function should work with any
regression function that follows the syntax of lm (others will need
adjustments). Note that you would have to create the interactions terms by
hand (which is no big deal if there are just few). Note also that this
approach can
Oh, if plot does the thing, then you just want to specify the color argument
accordingly, where the color argument is given by your production figure.
x=seq(1:100)
y=seq(1:100)
x.coord=sample(x,100)
y.coord=sample(y,100)
production=sample(1:100, 100)
plot(y.coord~x.coord)
#now lets say we
Does anything speak against selecting only x where x$B20 and then splitting
it by x$C?
split(x[!x$B20,],x$C)
HTH,
Daniel
--
View this message in context:
http://r.789695.n4.nabble.com/Split-data-frame-by-conditional-and-column-at-the-same-time-tp2197908p2216072.html
Sent from the R help
Are you asking us to do your homework? This is not a homework list.
For the t-test look in any introductory R manual. For the histograms, look
in the lattice library.
HTH
Daniel
--
View this message in context:
http://r.789695.n4.nabble.com/More-complex-historgram-tp2197823p2216076.html
Sent
Hi, assuming your production figures are in a square matrix, where points
with no production take zero and points with production take the production
figure, you could use
image()
This is the most basic approach I would think.
Daniel
--
View this message in context:
There is too little information to answer your question definitively.
However, an obvious reason is that you want to apply the function over
columns of a data.frame, which is done with apply(), but you try to apply
the function over elements of a list using lapply(). A list is not a
data.frame
Xin, you plot the scatterplot wrongly.
Note that the lm (your OLS regression) has a wiggle, whereas you plot
command has a comma. The plot command also should have a wiggle so that you
plot y against x and not x against y. See example below:
x=rnorm(100);e=rnorm(100)
y=2*x+e
reg=lm(y~x)
Just a quick addendum: You actually plot the line. If it is not in the graph
then just because it is outside the limits of the plotting region. But since
it's the right line on the wrong plot, it does not matter anyway. You need
to get the plot right first, which you do in the way I described
Fair enough, my mistake. However, I am quite fascinated how that focuses
everybody else on picking on the intitial answer and diverts everybody away
from anwering the actual question. All the more it points to the second
paragraph of my reply, namely that all modular components of the function
RE models are available in the lme4 and MASS packages in the glmer and
glmmPQL functions, respectively.
--
View this message in context:
http://r.789695.n4.nabble.com/Panel-data-with-binary-dependent-variable-tp2156043p2184223.html
Sent from the R help mailing list archive at Nabble.com.
if the plm function only puts out one r-squared, it should be the within
r-squared, but I could be wrong. Stata, for example, gives you a within, a
between, and an overall r-squared. Here is what they do.
set.seed(1)
x=rnorm(100)
fe=rep(rnorm(10),each=10)
id=rep(1:10,each=10)
ti=rep(1:10,10)
There is the plm package for linear panel models. Further, since estimation
of fixed effects models rests on the within-subject or -object variance, the
R-squared of interest is typically the within R-squared, not the overall or
between R-squared. Read up about it before you use it though.
Hi, even after rereading, I have little of a clue what it is exactly that you
are trying to do. It'd help if you provided a more concise, step-by-step
description and/or the smallest unambiguous example of the two tables AND of
what should come out at the end. Also, unless for relatively trivial
Hi, type
?cor
and hit ENTER.
More generally, since you seem to be a newbie to R, I would suggest that you
pick-up one of the many manuals to R that are available online and that you
make yourself familiar with the posting guide for this list.
Best,
Daniel
-
cuncta
Hi, on the one hand, you write fairly large, on the other hand, you write
should be readable by anything. The warnings indicate that you are plain
out of memory at some point. Not too surprising, given that your dataset has
about 45 rows and 720 columns. You may search the r-help files first
Hi Matt, see the example below. It took me a while to figure it out. I
suggest you carefully examine the example step by step. It computes t-values
for dataset with 3 variables and 8 unique combinations of two binning
variables. The code should extend easily to larger datasets. Also, it uses
the
Gallon, your question looks very homeworky. People on this list are not
likely to help you unless you can demonstrate own effort (even if it
failed), and the list is not for homework questions in case it is one. Where
exactly are you stuck?
Daniel
-
cuncta stricte
Hi Xin, to answer your question: say you have your regression
reg = coxph(...
Then you can assess the log likelihood by
reg$loglik
This vector contains typically two values, the null log likelihood of the
restricted model that excludes the fixed effects and the log likelihood of
the
Amit, how to color or label your pca plot has been answered before. Look at
this post: http://n4.nabble.com/PCA-analysis-td861508.html#a861509
As for your problem, it's hard to say what went wrong without having the
data. You write, there is nothing plotted in the graph. Does that mean you
get a
?hist shows you the options
-
cuncta stricte discussurus
-
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of casperyc
Sent: Friday, April 16, 2010 3:56 PM
To: r-help@r-project.org
I think this requires you to just pick up a manual / introductory book on
R/regression in R, of which there are many on the internet / in the
bookstores, respectively. Every manual I have seen has at least examples for
quadratics. And extensions to other functional forms are straightforward.
This reads like homework. You should show some evidence where you are stuck
or pick up an R book/manual/introduction after which you should be able to
do this yourself quite easily.
Daniel
-
cuncta stricte discussurus
-
-
Assume you have suitable week indicator and your data is stored in a
data.frame named data. Then you get the weekly averages by
#simulate data
week - rep(1:52,each=7)
x - week+rnorm(52*7,)
y - rev(week)+rnorm(52*7)
#create data frame
data=data.frame(week,x,y)
#get weekly averages in a list
Hi, nothing customized is effortless. It typically requires a bit of coding
unless you are lucky and somebody has implemented it in some package (you
just have to find the package). But it's not that difficult to do it
yourself. It just requires figuring out where the lines should be placed,
I may be mistaken, but I don't think that's possible or even should be
possible. A matrix is m x n, where m and n are (kind of fixed) integers. You
cannot have a matrix where m(1) to m(n) (the row lengths) vary. If you want
to do this, you have to use a list instead (I believe).
As a poor
This is about the covariates, not the dependent variable. So a polynomial
logistic regression seems hardly appropriate.
David is right with his latest statement, just because they are ordered does
not assure that the effect is monotonic. If the low, medium, and high
groups had even spacing
If the flight identifiers runway$Flight and oooi$Flight are unique (i.e.
only one observation has the same identifier in each dataset), you could use
merge() to bind together the dataset based on matching the two. See,
?merge
Also, I see an OnDate variable in both dataset. So if Flight does not
101 - 200 of 457 matches
Mail list logo