Running ‘testthat.R’ [49s/49s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # Had the same issue as in this thread: https://github.com/hadley/testthat/issues/86
  > Sys.setenv("R_TESTS" = "")
  > 
  > testthat::test_check("dynamichazard", reporter = "summary")
  Loading required package: dynamichazard
  Loading required package: survival
  Tracing function "expect_known_value" in package "testthat"
  Tracing function "expect_known_output" in package "testthat"
  Loading required package: DBI
  Running tests for GMA: ..................
  Testing LAPACK wrapper functions: ....................................
  Running test_PF: SSS......SS
  Testing SMA: .................................
  Testing UKF: .........................
  Testing bigglm_wrapper: ....123
  Testing boot: ...S..................................................................................................................................................................................................................................................................................................................................................................................................................
  Testing cpp sampling functions: ..................................................................................................................................................................................................................................................................................................................................................................................................................S.............................................................
  Running test_cpp_utils.R:: SS...
  Testing ddhazard w/ generic things and w/ the the EKF : ..............S..............
  Testing design_mat_and_risk_obj: ................................................................S.................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
  Testing fixed_effects_in_E_step: .........
  Testing test_fixed_effects_in_M_step: 4.5......S6
  Running tests for hatvalues: ....
  Testing loglike: ........................
  Testing options: .
  Testing parallelglm vs. glm: ................................S
  Testing plot functions: ......................................
  Testing predict: .............................................................S
  Testing print function: ...SS....
  Testing residuals functions: ..................................................................................................................................................................................................SS
  Testing shiny app: ..
  Testing static_glm: ....................
  Testing summary function: .................
  Testing test_utils: ............S......
  Testing weights in fit: ................
  
  ══ Skipped ═════════════════════════════════════════════════════════════════════
  1. dmvnrm_log_test gives correct likelihood (@test_PF.R#4) - mvtnorm cannot be loaded
  
  2. PF_smooth gives same results (@test_PF.R#35) - On CRAN
  
  3. Import and export PF cloud from Rcpp gives the same (@test_PF.R#222) - On CRAN
  
  4. PF_EM gives previous results on head neck data set (@test_PF.R#300) - On CRAN
  
  5. compute_summary_stats gives previous results (@test_PF.R#357) - On CRAN
  
  6. boot yields previously computed values with pbc (@test_boot_est.R#19) - On CRAN
  
  7. mvrnorm gives expected sample mean and variance (@test_cpp_sample_funcs.R#54) - On CRAN
  
  8. lambert_W0 gives close to same results as gsl::lambert_W0 (@test_cpp_utils.R#4) - gsl cannot be loaded
  
  9. trunc_lp_in_exponential_dist does not truncate when not needed (@test_cpp_utils.R#12) - On CRAN
  
  10. Different non-integer time_scales gives the same result with ddhazard (@test_ddhazard_n_EKF.R#136) - On CRAN
  
  11. Different forms of fixing the intercept gives same results (@test_design_mat_and_risk_obj.R#111) - On CRAN
  
  12. posterior_approx gives previous found values with fixed effects in M-step (@test_fixed_effects_in_M_step.R#168) - On CRAN
  
  13. glm and parallelglm gives the same (@test_parallelglm.R#61) - On CRAN
  
  14. Different non-integer time_scales gives the same result with predict results (@test_predict.R#367) - On CRAN
  
  15. print.ddhazard_boot gives the expected output (@test_print.R#39) - On CRAN
  
  16. Print function for PF objects gives previous results (@test_print.R#87) - On CRAN
  
  17. Gets previous results with Rossi (@test_residuals.R#210) - On CRAN
  
  18. Get prevoius residuals with whas500 (@test_residuals.R#236) - On CRAN
  
  19. Testing util functions to sim series for tests (@test_test_utils.R#28) - On CRAN
  
  ══ Failed ══════════════════════════════════════════════════════════════════════
  ── 1. Error: bigglm and my c++ version yields similar results (@test_bigglm_wrap
  no applicable method for 'bigglm' applied to an object of class "function"
  1: suppressWarnings(bigglm_res <- biglm::bigglm(form, get_data_func, family = if (model == 
         "logit") binomial() else poisson())) at testthat/test_bigglm_wrapper.R:266
  2: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
  3: biglm::bigglm(form, get_data_func, family = if (model == "logit") binomial() else poisson())
  4: biglm::bigglm(form, get_data_func, family = if (model == "logit") binomial() else poisson())
  
  ── 2. Error: bigglm and my c++ version yields similar results with offsets (@tes
  no applicable method for 'bigglm' applied to an object of class "function"
  1: suppressWarnings(bigglm_res <- biglm::bigglm(form, get_data_func, family = if (model == 
         "logit") binomial() else poisson())) at testthat/test_bigglm_wrapper.R:285
  2: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
  3: biglm::bigglm(form, get_data_func, family = if (model == "logit") binomial() else poisson())
  4: biglm::bigglm(form, get_data_func, family = if (model == "logit") binomial() else poisson())
  
  ── 3. Error: bigglm and my c++ version yields similar with weights (@test_bigglm
  no applicable method for 'bigglm' applied to an object of class "function"
  1: suppressWarnings(bigglm_res <- biglm::bigglm(form, get_data_func, family = if (model == 
         "logit") binomial() else poisson(), weights = ~ws)) at testthat/test_bigglm_wrapper.R:308
  2: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
  3: biglm::bigglm(form, get_data_func, family = if (model == "logit") binomial() else poisson(), 
         weights = ~ws)
  4: biglm::bigglm(form, get_data_func, family = if (model == "logit") binomial() else poisson(), 
         weights = ~ws)
  
  ── 4. Error: Only fixed effects yields same results as bigglm with logit model (
  no applicable method for 'bigglm' applied to an object of class "data.frame"
  1: suppressWarnings(res2 <- bigglm(update(form, Y ~ . - ddFixed_intercept()), data = tmp_design$X, 
         family = binomial(), chunksize = 1000)) at testthat/test_fixed_effects_in_M_step.R:24
  2: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
  3: bigglm(update(form, Y ~ . - ddFixed_intercept()), data = tmp_design$X, family = binomial(), 
         chunksize = 1000)
  4: bigglm(update(form, Y ~ . - ddFixed_intercept()), data = tmp_design$X, family = binomial(), 
         chunksize = 1000)
  
  ── 5. Error: Only fixed effects yields same results as bigglm with exponential m
  no applicable method for 'bigglm' applied to an object of class "data.frame"
  1: suppressWarnings(res2 <- bigglm(update(form, Y ~ . - ddFixed_intercept() + offset(log(pmin(tstop, 
         t) - pmax(tstart, t - 1)))), data = tmp_design$X, family = poisson(), chunksize = 1000, 
         tolerance = 1e-04)) at testthat/test_fixed_effects_in_M_step.R:65
  2: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
  3: bigglm(update(form, Y ~ . - ddFixed_intercept() + offset(log(pmin(tstop, t) - pmax(tstart, 
         t - 1)))), data = tmp_design$X, family = poisson(), chunksize = 1000, tolerance = 1e-04)
  4: bigglm(update(form, Y ~ . - ddFixed_intercept() + offset(log(pmin(tstop, t) - pmax(tstart, 
         t - 1)))), data = tmp_design$X, family = poisson(), chunksize = 1000, tolerance = 1e-04)
  
  ── 6. Error: Only fixed effects yields same results as bigglm with exponential m
  no applicable method for 'bigglm' applied to an object of class "data.frame"
  1: suppressWarnings(res2 <- bigglm(update(form, Y ~ . - ddFixed_intercept() + offset(log(pmin(tstop, 
         t) - pmax(tstart, t - 1)))), data = tmp_design$X, family = poisson(), chunksize = 1000, 
         tolerance = 1e-04, weights = ~ws)) at testthat/test_fixed_effects_in_M_step.R:207
  2: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
  3: bigglm(update(form, Y ~ . - ddFixed_intercept() + offset(log(pmin(tstop, t) - pmax(tstart, 
         t - 1)))), data = tmp_design$X, family = poisson(), chunksize = 1000, tolerance = 1e-04, 
         weights = ~ws)
  4: bigglm(update(form, Y ~ . - ddFixed_intercept() + offset(log(pmin(tstop, t) - pmax(tstart, 
         t - 1)))), data = tmp_design$X, family = poisson(), chunksize = 1000, tolerance = 1e-04, 
         weights = ~ws)
  
  ══ DONE ════════════════════════════════════════════════════════════════════════
  Error: Test failures
  Execution halted