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Error in bootstrapSE

Ask questions about errors you encouunter. Please make sure to include full details about your model specifications, and ideally your model file.
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intllawKuma
Posts: 4
Joined: 29 Apr 2022, 08:06

Error in bootstrapSE

Post by intllawKuma » 29 Apr 2022, 09:08

Hello,

I modified "LC_with_covariates" in Example Files and tried to estimate bootstrap standard errors.
However, I got the following error message:

Error in apollo_preprocess(inputs = mnl_settings, modelType, functionality, : Each element of "utilities" for model component "Class_1" needs to be a scalar or a vector/matrix/cube with one row per observation in the "database"

I would appreciate it if you could tell me what is wrong with the following code.

Code: Select all


library(apollo)
apollo_initialise()
apollo_control = list(
  modelName       = "LC_with_covariates",
  modelDescr      = "LC model with covariates",
  indivID         = "ID",
  nCores          = 3, 
  outputDirectory = "output"
)
database = apollo_swissRouteChoiceData

apollo_beta = c(asc_1           = 0,
                asc_2           = 0,
                beta_tt_a       = 0,
                beta_tt_b       = 0,
                beta_tc_a       = 0,
                beta_tc_b       = 0,
                beta_hw_a       =-0.0396,
                beta_hw_b       =-0.0479,
                beta_ch_a       =-0.7624,
                beta_ch_b       =-2.1725,
                delta_a         = 0.0329,
                gamma_commute_a = 0,
                gamma_car_av_a  = 0,
                delta_b         = 0,
                gamma_commute_b = 0,
                gamma_car_av_b  = 0)

apollo_fixed = c("asc_2","delta_b","gamma_commute_b","gamma_car_av_b")

apollo_lcPars=function(apollo_beta, apollo_inputs){
  lcpars = list()
  lcpars[["beta_tt"]] = list(beta_tt_a, beta_tt_b)
  lcpars[["beta_tc"]] = list(beta_tc_a, beta_tc_b)
  lcpars[["beta_hw"]] = list(beta_hw_a, beta_hw_b)
  lcpars[["beta_ch"]] = list(beta_ch_a, beta_ch_b)
  
  ### Utilities of class allocation model
  V=list()
  V[["class_a"]] = delta_a + gamma_commute_a*commute + gamma_car_av_a*car_availability
  V[["class_b"]] = delta_b + gamma_commute_b*commute + gamma_car_av_b*car_availability
  
  ### Settings for class allocation models
  classAlloc_settings = list(
    classes      = c(class_a=1, class_b=2), 
    utilities    = V  
  )
  
  lcpars[["pi_values"]] = apollo_classAlloc(classAlloc_settings)
  
  return(lcpars)
}

apollo_inputs = apollo_validateInputs()

apollo_probabilities=function(apollo_beta, apollo_inputs, functionality="estimate"){
    
  ### Attach inputs and detach after function exit
  apollo_attach(apollo_beta, apollo_inputs)
  on.exit(apollo_detach(apollo_beta, apollo_inputs))

  ### Create list of probabilities P
  P = list()
  
  ### Define settings for MNL model component that are generic across classes
  mnl_settings = list(
    alternatives = c(alt1=1, alt2=2),
    avail        = list(alt1=1, alt2=1),
    choiceVar    = choice
  )
  
  ### Loop over classes
  for(s in 1:2){
    
    ### Compute class-specific utilities
    V=list()
    V[["alt1"]]  = asc_1 + beta_tc[[s]]*tc1 + beta_tt[[s]]*tt1 + beta_hw[[s]]*hw1 + beta_ch[[s]]*ch1
    V[["alt2"]]  = asc_2 + beta_tc[[s]]*tc2 + beta_tt[[s]]*tt2 + beta_hw[[s]]*hw2 + beta_ch[[s]]*ch2
    
    mnl_settings$utilities     = V
    mnl_settings$componentName = paste0("Class_",s)
    
    ### Compute within-class choice probabilities using MNL model
    P[[paste0("Class_",s)]] = apollo_mnl(mnl_settings, functionality)
    
    ### Take product across observation for same individual
    P[[paste0("Class_",s)]] = apollo_panelProd(P[[paste0("Class_",s)]], apollo_inputs ,functionality)
    
  }
  
  ### Compute latent class model probabilities
  lc_settings  = list(inClassProb = P, classProb=pi_values)
  P[["model"]] = apollo_lc(lc_settings, apollo_inputs, functionality)
  
  ### Prepare and return outputs of function
  P = apollo_prepareProb(P, apollo_inputs, functionality)
  return(P)
}

model = apollo_estimate(apollo_beta, apollo_fixed, apollo_probabilities, apollo_inputs,estimate_settings=list(bootstrapSE=30))
apollo_modelOutput(model, list(printPVal=2))


dpalma
Posts: 136
Joined: 24 Apr 2020, 17:54

Re: Error in bootstrapSE

Post by dpalma » 12 May 2022, 16:49

Hi,

You seem to have found a bug. This has been corrected in v0.2.8. That version is not released yet, but you can download it from this link (for windows).

Once you downloaded the file, you can installing using RStudio by going to Tools > Install packages... . Then, in the "Install From" field select "Package Archive file" and select the downloaded file in the file selection window that just opened. Then click the "Install" button.

Also, I recommend running the model using a single core. Using multiple cores is particularly beneficial for models with random coefficients or error terms. Not so much for simple latent class models.

Cheers
David

intllawKuma
Posts: 4
Joined: 29 Apr 2022, 08:06

Re: Error in bootstrapSE

Post by intllawKuma » 19 May 2022, 05:53

Dear Dr. Palma,

I successfully got bootstrap standard errors by v0.2.8 that I downloaded from your link.
Thank you.

rupch22
Posts: 2
Joined: 31 May 2022, 23:45

Re: Error in bootstrapSE

Post by rupch22 » 31 May 2022, 23:48

Tried executing this with the unreleased version, yet getting this error.
Estimation cycle 1 (8532 obs)
#############################################################################################
The scaling of the model led to differences in the results, and was thus not used.
This is unexpected. You may want to contact the developers.

... current process will resume in 5 seconds unless interrupted by the user
#############################################################################################
Error in stats::cov(paramStack[includeRow, ]) :
supply both 'x' and 'y' or a matrix-like 'x'
In addition: There were 24 warnings (use warnings() to see them)
###############################################################
Insights are welcome. Thank you

dpalma
Posts: 136
Joined: 24 Apr 2020, 17:54

Re: Error in bootstrapSE

Post by dpalma » 29 Jun 2022, 20:43

Hi,

Sorry for the belated reply.

You are right, there was a bug in the file I gave you access to. That bug has been fixed in the current version, which you can download from the following links:
Windows
Linux
The mac version will be uploaded to the webpage soon.

Cheers
David

rupch22
Posts: 2
Joined: 31 May 2022, 23:45

Re: Error in bootstrapSE

Post by rupch22 » 22 Jul 2022, 11:26

Hi Dr Palma,
I can't find the version you attached. Could you please attach it again?

Best regards

dpalma
Posts: 136
Joined: 24 Apr 2020, 17:54

Re: Error in bootstrapSE

Post by dpalma » 09 Aug 2022, 16:56

Hi,

Sorry about that, the file was probably updated so the link stopped working. Please try one of the following:
Windows
Linux (source)
macOS

Anyhow, v0.2.8 should be available from CRAN in the next few days.

Cheers
David

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