-
Notifications
You must be signed in to change notification settings - Fork 22
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
meta() support #130
Comments
Several questions about meta
> sub_list <- list(a = hrange_list_same_grid[1:3], b = hrange_list_same_grid[4:6])
> meta(sub_list)
* Sub-population a
ΔAICc
Dirac-\u03b4 0
inverse-Gaussian Inf
* Sub-population b
ΔAICc
Dirac-\u03b4 0
inverse-Gaussian Inf
* Joint population
ΔAICc
inverse-Gaussian 0.0000000
Dirac-\u03b4 0.9497466
* Joint population versus sub-populations (best models)
ΔAICc
Joint population 0.000000
Sub-population 2.634796
, , low
/a /b
a/ 1.0000000 0.6384834
b/ 0.7848531 1.0000000
, , est
/a /b
a/ 1.000000 0.9124752
b/ 1.112321 1.0000000
, , high
/a /b
a/ 1.000000 1.256063
b/ 1.541884 1.000000
|
There's no need to worry about There are two usages of
|
OK. for 2nd mode, do you want to always use mean = FALSE, or make it an option and default to false? , , low
/a /b
a/ 1.0000000 0.6384834
b/ 0.7848531 1.0000000 |
I would make
|
I'm seeing
In ctmm code it seemed to be just "Dirac-d" but I don't know why it print out as this. |
Did you upgrade to R 4.0.4? There is a known bug that is supposed to be addressed in the next release. |
Yes I'm on R 4.0.4. That seemed to be the cause. ΔAICc
inverse-Gaussian 0.0000000
Dirac-\u03b4 0.9497455
low est high
mean (km2) 2.753858e+02 380.21059001 507.2465737
CoV2 (RVAR) 3.124238e-03 0.08161385 0.2835524
CoV (RSTD) 6.166569e-02 0.31517625 0.5874734 For the meta output, originally I plan to convert to a data.frame and show in a table, just like the model selection table. Though the first 2 lines and the other parts seemed to be different things, not easy to organize in same table. A simple and brutal method is just print the output in a text box in app as is, not using a html table. Or maybe I can create 2 tables side by side as html table. I'll need some name/description on each table. The advantage of just print the text vs make html table is that if there is change in meta output I don't need to change my side of code. With html table I need to assume something about output structure and names etc, which could change with ctmm updates. |
I think the first table is just printed to the console and is just there for information purposes—mainly to see if variance estimation failed. The second table is the returned object and contains the important outputs. |
So I can ignore the first table in the app? Besides, there was a warning in calculating home range, should I add some parameter to avoid the warning? I didn't see DOP in help page of
|
I think the first table is fine to leave in the console. It's more for advanced users to tweak the The |
I imported buffalo like before, didn't turn on error specifically. How to check if location error is on? The data was imported and recognized as not calibrated. |
I'm not getting this message with the most recent version of the package, if not having location error turned on... and it isn't turned on by default. |
More specifically, how to turn on location error? So that I can check my code and session to see if it was turned on. On meta of sub-population, the sub-population cannot have single individual, otherwise there will be error. Is this expected? If it's expected, I can set some condition to prevent it happen but will need to explain to user each sub-population need to have at least 2 individuals. |
If the GUESS object has a non-zero error slot (in any component), then error is turned on. Normal users would not assign only 1 member to a population, but I can fix this error to not occur. |
It took me quite some time to track down the warning was generated in plotting telemetry data, not home range (my home range plot plot location together). > library(ctmm)
> data("buffalo")
> plot(buffalo)
DOP values missing. Assuming DOP=1.
DOP values missing. Assuming DOP=1.
DOP values missing. Assuming DOP=1.
DOP values missing. Assuming DOP=1.
DOP values missing. Assuming DOP=1.
DOP values missing. Assuming DOP=1. Looks like buffalo data have some UERE value. Is this the reason?
|
Now I have the features mentioned implemented. I'm still not satisfied with the UI, but I don't want to spend further time to change it before we can discuss it in next meeting. |
This is expected now. Location error is now turned on by default in plot() and a default UERE object is now assigned on import, but with DOF=0, which makes it do nothing but assign a guess value (which plot and outlie use before calibration). Previously, users were not realizing that they could plot the location errors and users with e-obs (or similar) data were plotting or assessing outliers with inappropriate guess values. |
The app allows user to select multiple models of same individual for home range, then we need to identify them in the meta plot. Previously I used individual name + model name in this case, but this will make the meta plot axis label too small. @chfleming Can you make the axis label with fixed font or adjust the margin so it can take longer individual names? I think sometimes the user data also may have long name so this is needed anyway. You can test the plot by just making some long names. I can also remove the "home range" part in the name above to make it shorter, but the model name is needed so in total we need at least 22-25 characters in name. |
If you increase the margin, then the font size should increase up unto the default size. I coded it to only shrink the font when the margin is too narrow and fill the margin. Also, with ~50 individuals, I find it nice to have the font a bit smaller. I pushed an update so that (1) |
Newer versions of
ctmm
have themeta()
command forUD
objects (see?meta
). It would be nice to have it supported inctmmweb
. There are two basic ways to use this function. You can either runmeta()
on a list of all of the individuals, likemeta(list(...))
, or you can run it on a list of lists, where each sub-list is a group like males or females to compare, likemeta(list(male=list(...),female=list(...))
.The text was updated successfully, but these errors were encountered: