marginals for linear predictor

[Thierry Onkelinx]

Dear all,

Adding the argument control.compute = list(waic = TRUE) or control.predictor = list(compute = TRUE) added the marginals for the fitted values and the linear predictor to the output.

This no longer works starting from version 21.07.10-1. Is this intentional? 

Best regards,

Thierry

ir. Thierry Onkelinx

Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry....@inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

///////////////////////////////////////////////////////////////////////////////////////////

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey
///////////////////////////////////////////////////////////////////////////////////////////

[Helpdesk]

yes, this change is intentional. adding the marginals of the linear predictors take normally a lot of space, hence it is now by default omitted even though it is computed internally. the summary statistics are there though.

here is how to enable that if you want to.

> r <- inla(y~1,data=data.frame(y=0), control.predictor=list(compute=TRUE))

> r$summary.linear.predictor

mean sd 0.025quant

Predictor.00000001 -7.063925267e-08 0.01584127732 -0.03109767579

0.5quant 0.975quant mode kld

Predictor.00000001 -1.77083949e-06 0.0311065814 7.726823128e-07 0.1048790746

> r$marginals.linear.predictor

NULL

> r <- inla(y~1,data=data.frame(y=0), control.predictor=list(compute=TRUE), control.compute=list(return.marginals.predictor=TRUE))

> r$summary.linear.predictor

mean sd 0.025quant

Predictor.00000001 -7.063925267e-08 0.01584127732 -0.03109767579

0.5quant 0.975quant mode kld

Predictor.00000001 -1.77083949e-06 0.0311065814 7.726823128e-07 0.1048790746

> r$marginals.linear.predictor

$Predictor.1

x y

[1,] -2.178148180e-01 1.411929654e-05

[2,] -2.094460017e-01 5.740707540e-04

[3,] -2.079734256e-01 6.216378795e-04

[4,] -1.969516747e-01 1.032968814e-03

[5,] -1.742518544e-01 2.669343824e-03

[6,] -1.601479432e-01 4.692449841e-03

[7,] -1.306888908e-01 1.446254770e-02

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[Thierry Onkelinx]

OK. Thanks for the clarification. Adding the extra argument solved my problem.

ir. Thierry Onkelinx

Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry....@inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

///////////////////////////////////////////////////////////////////////////////////////////

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey
///////////////////////////////////////////////////////////////////////////////////////////

Op vr 3 sep. 2021 om 12:52 schreef Helpdesk <he...@r-inla.org>: