In addition to what Rolf said, a relatively obscure but generally
useful way to "globally" control fontsize is to set the underlying
grid parameter (see ?grid::gpar). The easiest way to do this is
through the lattice settings, e.g.,
lattice.options(default.theme = list(grid.pars = list(cex = 1.5))
Further to yesterday's posts:
I think the "n" value would be the maximum possible number of jumps,
not the number of students.
In theory, the minimum possible number is zero, so the distributions
are more binomial-like than they look.
Also, there was a mistake in my comments.
The jump is from non-
On Sat, 27 Mar 2021 21:26:53 +
Yuan Chun Ding wrote:
> Dear R user,
>
> The following qqunit.plot function generated correct qq plot,
> however, I want to make axis label (1 ,2 ,.8) have larger size
> for publication. I tried to add cex.axis =1.2 code following the pch
> =20, but it d
Dear R user,
The following qqunit.plot function generated correct qq plot, however, I want
to make axis label (1 ,2 ,.8) have larger size for publication. I tried to
add cex.axis =1.2 code following the pch =20, but it does not change size of
axis label. I guess lattice library setting is
Hi Mahmood,
What you have specified can be done with:
col=c(rep("black",10),rep("red",10))
depending upon what print function you are using. I suspect that this
may be based on a value in your data. For example, if you want black
for values of some variable up to 10 and red for those over:
col=
David: Note that your problem is linear so it looks like you can use the lm
function to estimate a, b and c. ( or as a check against what john
did ) Unless I'm missing something which could be the case ! Also, see
Bloomfield's text for a closed form solution. I think it's
called "Intro To Four
Dear David,
I'm afraid that this doesn't make much sense -- that is, I expect that
you're not doing what you intended.
First, sin(2*pi*t) and cos(2*pi*t) are each invariant:
> sin(2*pi*t)
[1] -2.449294e-16 -4.898587e-16 -7.347881e-16 -9.797174e-16
-1.224647e-15 -1.469576e-15
[7] -1.714506e
Use nlsr::nlxb() to get analytic derivatives. Though your problem is pretty
rubbishy --
look at the singular values. (You'll need to learn some details of nlxb()
results to
interpret.)
Note to change the x to t in the formula.
JN
> f1 <- y ~ a+b*sin(2*pi*t)+c*cos(2*pi*t)
> res1 <- nls(f1, dat
Hello all,
I have seen instructions for conducting post-hoc pairwise comparisons in R
after running an ANOVA, Kruskal-Wallis Test, or Yuen�s Test.
Is there a method to subset data automatically to run an effect size test
across different pairs? For example, if I want to run Cohen�s d to examine
I'm trying to fit a harmonic equation to my data, but when I'm applying the
nls function, R gives me the following error:
Error in nlsModel(formula, mf, start, wts) : singular gradient matrix at
initial parameter estimates.
All posts I've seen, related to this error, are of exponential function
Hi
I use this command to generate a graph of individuals
ind <- get_famd_ind(res.famd)
fviz_famd_ind(res.famd, repel = TRUE)
I would like to know how can I specify different colors for different
individuals?
The colorization is not very complex. Basically, I want to specify rows[1:10]
to be
On Fri, 26 Mar 2021, Greg Minshall wrote:
My malpractice insurance gives me a discount if I consult up to 22
hours per week in a 3 months period.
i wonder if you might add up the number of hours worked over the (92 (?))
days of November, December, January, divide by that number of days, then
d
Eberhard,
> My malpractice insurance gives me a discount if I consult up to 22
> hours per week in a 3 months period.
i wonder if you might add up the number of hours worked over the (92
(?)) days of November, December, January, divide by that number of
days, then divide by seven? that would
Stefano,
my contribution is similar to Bill Dunlap's:
x <- c(1,0,0,0,2,2,3,4,0,1,1,0,5,5,5,0,1)
(cumsum(rle(x)$lengths)-(rle(x)$length-1))[which(diff(diff(rle(x)$values)>=0)<0)+1]
cumsum(rle(x)$lengths)[which(diff(diff(rle(x)$value)>0)>0)+1]
kind of a cute little problem, actually.
che
Sorry.
I just realized, after posting, that the "n" value in the dispersion
calculation isn't correct.
I'll have to revisit the simulation, tomorrow.
On Sat, Mar 27, 2021 at 9:11 PM Abby Spurdle wrote:
>
> Hi Rolf,
>
> Let's say we have a course called Corgiology 101, with a single moderated
> e
Hi Rolf,
Let's say we have a course called Corgiology 101, with a single moderated exam.
And let's say the moderators transform initial exam scores, such that
there are fixed percentages of pass rates and A grades.
Rather than count the number of passes, we can count the number of "jumps".
That i
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