Problem with me() function

[Sam Bashevkin]

Hi,

I'm trying to use the me() function to include predictors with measurement error. When I include this function, I'm getting an error in parsing the Stan model. Here's a simplified version of my model formula with the error message below. I've also tried inputting a vector for the sd instead of the "0.023" and I get the same error. I'd prefer to use a vector if possible since I know the measurement error varies through the data. 

Successes|trials(trials) ~ Predictor1 + me(Predictor2, sdx = 0.023), family=binomial()

SYNTAX ERROR, MESSAGE(S) FROM PARSER:

No matches for: 

  normal_rng(vector, vector)

Available argument signatures for normal_rng:

  normal_rng(real, real)

  error in 'model9fbb19cce93c_file9fbb7b8bd6f2' at line 61, column 46

  -------------------------------------------------

    59:   real prior_temp_Intercept = normal_rng(0,5); 

    60:   real prior_bme = normal_rng(0,5); 

    61:   real prior_Xn_1 = normal_rng(Xme_1,noise_1); 

                                                     ^

    62:   real prior_b_Intercept = prior_temp_Intercept - dot_product(means_X, b); 

  -------------------------------------------------

Error in stanc(model_code = paste(program, collapse = "\n"), model_name = model_cppname,  : 

  failed to parse Stan model 'file9fbb7b8bd6f2' due to the above error.

R version 3.4.4 (2018-03-15)

Platform: x86_64-apple-darwin15.6.0 (64-bit)

Running under: macOS High Sierra 10.13.3

brms_2.1.0

rstan_2.17.3

Thank you very much,

Sam

[Paul Buerkner]

Thanks for reporting. This error occurs only if sample_prior = TRUE and it should be fixed in the latest github version of brms now.

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