• using R Under development (unstable) (2019-12-04 r77519)
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• checking examples ... ERROR
  Running examples in 'DCchoice-Ex.R' failed
  The error most likely occurred in:
  
  > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
  > ### Name: dbchoice
  > ### Title: Parametric approach to analyze double-bounded dichotomous choice
  > ### contingent valuation data
  > ### Aliases: dbchoice print.dbchoice vcov.dbchoice logLik.dbchoice
  > ### Keywords: DCchoice double-bounded nonlinear
  >
  > ### ** Examples
  >
  > ## Examples are based on a data set NaturalPark in the package
  > ## Ecdat (Croissant 2011): DBDCCV style question for measuring
  > ## willingness to pay for the preservation of the Alentejo Natural
  > ## Park. The data set (dataframe) contains seven variables:
  > ## bid1 (bid in the initial question), bidh (higher bid in the follow-up
  > ## question), bidl (lower bid in the follow-up question), answers
  > ## (response outcomes in a factor format with four levels of "nn",
  > ## "ny", "yn", "yy"), respondents' characteristic variables such
  > ## as age, sex and income (see NaturalPark for details).
  > data(NaturalPark, package = "Ecdat")
  > head(NaturalPark)
    bid1 bidh bidl answers age sex income
  1 6 18 3 yy 1 female 2
  2 48 120 24 yn 2 male 1
  3 48 120 24 yn 2 female 3
  4 24 48 12 nn 5 female 1
  5 24 48 12 ny 6 female 2
  6 12 24 6 nn 4 male 2
  >
  > ## The variable answers are converted into a format that is suitable for the
  > ## function dbchoice() as follows:
  > NaturalPark$R1 <- ifelse(substr(NaturalPark$answers, 1, 1) == "y", 1, 0)
  > NaturalPark$R2 <- ifelse(substr(NaturalPark$answers, 2, 2) == "y", 1, 0)
  >
  > ## We assume that the error distribution in the model is a
  > ## log-logistic; therefore, the bid variables bid1 is converted
  > ## into LBD1 as follows:
  > NaturalPark$LBD1 <- log(NaturalPark$bid1)
  >
  > ## Further, the variables bidh and bidl are integrated into one
  > ## variable (bid2) and the variable is converted into LBD2 as follows:
  > NaturalPark$bid2 <- ifelse(NaturalPark$R1 == 1, NaturalPark$bidh, NaturalPark$bidl)
  > NaturalPark$LBD2 <- log(NaturalPark$bid2)
  >
  > ## The utility difference function is assumed to contain covariates (sex, age, and
  > ## income) as well as two bid variables (LBD1 and LBD2) as follows:
  > fmdb <- R1 + R2 ~ sex + age + income | LBD1 + LBD2
  >
  > ## Not run:
  > ##D ## The formula may be alternatively defined as
  > ##D fmdb <- R1 + R2 ~ sex + age + income | log(bid1) + log(bid2)
  > ## End(Not run)
  >
  > ## The function dbchoice() with the function fmdb and the dataframe
  > ## NP is executed as follows:
  > NPdb <- dbchoice(fmdb, data = NaturalPark)
  > NPdb
  
  Distribution: log-logistic
  (Intercept) sexfemale age income log(bid)
     3.490541 -0.267775 -0.351578 0.277374 -1.133728
  > NPdbs <- summary(NPdb)
   ----------- FAILURE REPORT --------------
   --- failure: the condition has length > 1 ---
   --- srcref ---
  :
   --- package (from environment) ---
  DCchoice
   --- call from context ---
  wtp(object = X, b = coef, bid = bid, dist = dist)
   --- call from argument ---
  if (class(object) == "sbchoice" | class(object) == "dbchoice") {
      X <- object$covariates
      b <- object$coefficients
      bid <- object$bid
      dist <- object$dist
  } else {
      X <- object
  }
   --- R stacktrace ---
  where 1: wtp(object = X, b = coef, bid = bid, dist = dist)
  where 2: summary.dbchoice(NPdb)
  where 3: summary(NPdb)
  
   --- value of length: 2 type: logical ---
  [1] FALSE FALSE
   --- function from context ---
  function (object, b = NULL, bid = NULL, dist = NULL)
  {
      if (class(object) == "sbchoice" | class(object) == "dbchoice") {
          X <- object$covariates
          b <- object$coefficients
          bid <- object$bid
          dist <- object$dist
      }
      else {
          X <- object
      }
      coef <- b
      names(coef) <- NULL
      npar <- length(coef)
      b <- coef[npar]
      Xb <- sum(colMeans(X) * coef[-npar])
      if (dist == "log-logistic") {
          func <- function(x) plogis(-(Xb + b * log(x)), lower.tail = FALSE)
          medianWTP <- exp(-Xb/b)
          meanWTP <- ifelse(abs(b) > 1, integrate(func, 0, Inf,
              stop.on.error = FALSE)$value, Inf)
          trunc.meanWTP <- integrate(func, 0, exp(max(bid)), stop.on.error = FALSE)$value
          adj.trunc.meanWTP <- integrate(func, 0, exp(max(bid)),
              stop.on.error = FALSE)$value/plogis(-(Xb + b * max(bid)))
      }
      else if (dist == "log-normal") {
          func <- function(x) pnorm(-(Xb + b * log(x)), lower.tail = FALSE)
          medianWTP <- exp(-Xb/b)
          meanWTP <- integrate(func, 0, Inf, stop.on.error = FALSE)$value
          trunc.meanWTP <- integrate(func, 0, exp(max(bid)), stop.on.error = FALSE)$value
          adj.trunc.meanWTP <- integrate(func, 0, exp(max(bid)),
              stop.on.error = FALSE)$value/pnorm(-(Xb + b * max(bid)))
      }
      else if (dist == "logistic") {
          func <- function(x) plogis(-(Xb + b * x), lower.tail = FALSE)
          medianWTP <- -Xb/b
          meanWTP <- integrate(func, 0, Inf, stop.on.error = FALSE)$value
          trunc.meanWTP <- integrate(func, 0, max(bid), stop.on.error = FALSE)$value
          adj.trunc.meanWTP <- integrate(func, 0, max(bid), stop.on.error = FALSE)$value/plogis(-(Xb +
              b * max(bid)))
      }
      else if (dist == "normal") {
          func <- function(x) pnorm(-(Xb + b * x), lower.tail = FALSE)
          medianWTP <- -Xb/b
          meanWTP <- integrate(func, 0, Inf, stop.on.error = FALSE)$value
          trunc.meanWTP <- integrate(func, 0, max(bid), stop.on.error = FALSE)$value
          adj.trunc.meanWTP <- integrate(func, 0, max(bid), stop.on.error = FALSE)$value/pnorm(-(Xb +
              b * max(bid)))
      }
      else if (dist == "weibull") {
          func <- function(x) pweibull(exp(-Xb - b * log(x)), shape = 1,
              lower.tail = FALSE)
          medianWTP <- exp(-Xb/b) * (log(2))^(-1/b)
          meanWTP <- ifelse(abs(b) > 1, exp(-Xb/b) * gamma(1 -
              1/b), Inf)
          trunc.meanWTP <- integrate(func, 0, exp(max(bid)), stop.on.error = FALSE)$value
          adj.trunc.meanWTP <- integrate(func, 0, exp(max(bid)),
              stop.on.error = FALSE)$value/pweibull(exp(-Xb - b *
              max(bid)), shape = 1)
      }
      output <- list(meanWTP = meanWTP, trunc.meanWTP = trunc.meanWTP,
          adj.trunc.meanWTP = adj.trunc.meanWTP, medianWTP = medianWTP)
      return(output)
  }
  <bytecode: 0x82a1fa0>
  <environment: namespace:DCchoice>
   --- function search by body ---
  Function wtp in namespace DCchoice has this body.
   ----------- END OF FAILURE REPORT --------------
  Error in if (class(object) == "sbchoice" | class(object) == "dbchoice") { :
    the condition has length > 1
  Calls: summary -> summary.dbchoice -> wtp
  Execution halted
• checking PDF version of manual ... OK
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• DONE

Status: 1 ERROR