Sent from Proton Mail Android
Kevin,
Looks like I sent the wrong URL
Try this instead.
https://www.biopharmaservices.com/blog/statistical-methods-the-conventional-approach-vs-the-simulation-based-approach/#:~:text=Both%20simulation,reliability%20of%20their%20statistical%20analyses
Best rega
Hi Kevin,
It might seem like simulation methods (bootstrapping and randomization) and
traditional formulas (Normal or t-distributions) are just two ways to do the
same job. So why learn both? Each approach has its own strengths, and
statisticians use both in practice.
Why do professionals use b
PM, Gregg Powell via R-help
wrote:
>
>
> Hello Christofer,
>
> That’s good information. Thanks for the precision.
> Think I can use this now to work on a script:
>
> Based on what you provided:
> 1. Two distinct sets of coefficients, β¹ and β², each associated with
Hello Christofer,
That’s good information. Thanks for the precision.
Think I can use this now to work on a script:
Based on what you provided:
1. Two distinct sets of coefficients, β¹ and β², each associated with the
logits for:
• P(Y≤1)P(Y ≤ 1)P(Y≤1)
• P(Y≤2)P(Y ≤ 2)P(Y≤2)
2. Separate sum co
Hello again Christofer,
This clarification changes the model structure somewhat significantly -it
shifts us from a standard cumulative logit model with proportional odds to a
non-parallel cumulative logit model, where each threshold has its own set of β
coefficients. At least, that is now my un
nt"), lin)) :
> > > NA/NaN/Inf in foreign function call (arg 5)
> > > ```
> > > How can I properly set this regression model?
> > > Thank you
> >
> > > On Wed, Apr 16, 2025 at 7:08 AM Luigi Marongiu marongiu.lu...@gmail.com
> &g
Christofer,
That was a detailed follow-up — you clarified the requirements precisely enough
providing a position to proceed from...
To implement this, a constrained optimization procedure to estimate an ordinal
logistic regression model is needed (cumulative logit), based on:
1. Estimated Cut
& Statistics
> > > University of Melbourne, VIC 3010 Australia
> > > Tel: (+61) 0403 138 955
> > > Email: a...@unimelb.edu.au
> > > Website: https://researchers.ms.unimelb.edu.au/~apro@unimelb/
> > >
> > > I acknowledge the Traditional Ow
Hello again Christofer,
Thanks for your thoughtful note — I’m glad the outline was helpful. Apologies
for the long delay getting back to you. Had to do a small bit of research…
Recommended Text on Ordinal Log-Likelihoods:
You're right that most online sources jump straight to code or canned
func
Christofer,
Given the constraints you mentioned—bounded parameters, no intercept, and a sum
constraint—you're outside the capabilities of most off-the-shelf ordinal
logistic regression functions in R like vglm or polr.
The most flexible recommendation at this point is to implement custom
likel
Take a look at this Luigi...
># The model is: logit(p) = β₀ + β₁*Cycles
># Where p is the probability (or normalized value in your case)
>
># The inverse function would be: Cycles = (logit⁻¹(p) - β₀)/β₁
># Where logit⁻¹ is the inverse logit function (also called the expit >function)
>
># Extract
there are ways to implement constraints on parameter estimates in ordinal
logistic regression in R. Here are a few approaches:
The rms package (Regression Modeling Strategies) by Frank Harrell offers the
lrm function which can handle constraints through its penalty parameter, though
it's primar
Hi Thomas,
Glad to hear the suggestion helped, and that switching to a `data.table`
approach reduced the processing time and memory overhead—15 minutes for one of
the smaller datasets is certainly better! Sounds like the adjustments you
devised, especially keeping the multicore approach for `ma
How is the server configured to handle memory distribution for individual
users. I see it has over 700GB of total system memory, but how much can be
assigned it each individual user?
AAgain - just curious, and wondering how much memory was assigned to your
instance when you were running R.
reg
Thomas,
I'm curious - what OS are you running this on, and how much memory does the
computer have?
Let me know if that code worked out as I hoped.
regards,
gregg
On Wednesday, December 11th, 2024 at 6:51 AM, Deramus, Thomas Patrick
wrote:
> About to try this implementation.
>
> As a foll
Hello Thomas,
Consider that the primary bottleneck may be tied to memory usage and the
complexity of pivoting extremely large datasets into wide formats with tens of
thousands of unique values per column. Extremely large expansions of columns
inherently stress both memory and CPU, and splitting
Need to kill some time, so thought I'd Opine.
Given the intent, as I understood it... to extract components from a quantile
regression (rq) object similar to how one might extract effects from an lm
object.
Since it seems effects() is not implemented for rq, here are some alternative
approach
; Best Regards,
> Ashim
>
> On Wed, Jun 15, 2022 at 8:28 PM Gregg Powell via R-help
> r-help@r-project.org wrote:
>
> > Have data sets where there are names, in the first column, client names in
> > the second, and Client start date in the third.
> >
>
klish to handle within base R but less so in
> >the tidyverse.
> >
> >For example, if I try to make a data.frame the normal way, the list gets
> >made into multiple columns and copied to each row. Not what was expected. I
> >think some tidyverse functionality does b
llianne Carantes"
$ : num 12
‐‐‐ Original Message ‐‐‐
On Tuesday, September 14th, 2021 at 8:32 PM, Jeff Newmiller
wrote:
> An atomic column of data by design has exactly one mode, so if any values are
> non-numeric then the entire column will be non-numeric. What does
&
> Stuck on this problem - How does one remove all rows in a dataframe that have
> a numeric in the first (or any) column?
>
> Seems straight forward - but I'm having trouble.
>
I've attempted to used:
VPN_Sheet1 <- VPN_Sheet1[!is.numeric(VPN_Sheet1$HVA),]
and
VPN_Sheet1 <- VPN_Sheet1[!i
>
> 2 B 2 NA
>
> 3 C 3 NA
>
> 4 D 4 NA
>
> 5 E 5 NA
>
> > df_D
>
> names values_B values_A
>
> 6 K 16 NA
>
> 7 L 17 NA
>
> 8 M 18 NA
>
> 9 N 19 NA
>
> 10 O 20 NA
>
> HTH, Bill.
>
> W. Michels, P
This is even complicated to write into a question
Have two data.frames (A and B)
data.frame A and B each have a name column. Want to compare A and B data.frame
to each other based on the values in the 'names' columns - for every name that
appears in dataframe A but not B, I want to copy th
This is even complicated to write into a question
Have two data.frames (A and B)
data.frame A and B each have a name column. Want to compare A and B data.frame
to each other based on the values in the 'names' columns - for every name that
appears in dataframe A but not B, I want to copy th
24 matches
Mail list logo
