Date: 2025-11-21

# Fast Deviance: Numerical Equality Checks

#### Frédéric Bertrand

#### 2025-11-21

We validate that the fast deviance evaluator matches the generic `gamlss.dist` density route (up to floating-point tolerance) across common families.

## What you’ll learn

- How to call `check_fast_vs_generic()` on fitted `gamlss` models and read the returned diagnostics.
- How to iterate over multiple families/generators to create a validation table.
- How to attempt the wide sweep helper for dozens of families while skipping unsupported ones gracefully.

    library(gamlss)
    library(SelectBoost.gamlss)

    set.seed(2025)
    n <- 4000
    families <- list(
      NO = gamlss.dist::NO(),
      PO = gamlss.dist::PO(),
      LOGNO = gamlss.dist::LOGNO(),
      GA = gamlss.dist::GA(),
      IG = gamlss.dist::IG(),
      LO = gamlss.dist::LO(),
      LOGITNO = gamlss.dist::LOGITNO(),
      GEOM = gamlss.dist::GEOM(),
      BE = gamlss.dist::BE()
    )
    gen_fun <- list(
      NO = function(n) gamlss.dist::rNO(n, mu = 0, sigma = 1),
      PO = function(n) gamlss.dist::rPO(n, mu = 2.5),
      LOGNO = function(n) gamlss.dist::rLOGNO(n, mu = 0, sigma = 0.6),
      GA = function(n) gamlss.dist::rGA(n, mu = 2, sigma = 0.5),
      IG = function(n) gamlss.dist::rIG(n, mu = 2, sigma = 0.5),
      LO = function(n) gamlss.dist::rLO(n, mu = 0, sigma = 1),
      LOGITNO = function(n) gamlss.dist::rLOGITNO(n, mu = 0, sigma = 1),
      GEOM = function(n) gamlss.dist::rGEOM(n, mu = 3),
      BE = function(n) gamlss.dist::rBE(n, mu = 0.4, sigma = 0.2)
    )

    summ <- lapply(names(families), function(fname) {
      fam <- families[[fname]]; gen <- gen_fun[[fname]]
      y <- gen(n); dat <- data.frame(y = y)
      fit <- try(gamlss::gamlss(y ~ 1, data = dat, family = fam), silent = TRUE)
      if (inherits(fit, "try-error")) return(NULL)
      chk <- check_fast_vs_generic(fit, dat, tol = 1e-6)
      data.frame(family = fname, ll_fast = chk$ll_fast, ll_generic = chk$ll_generic,
                 abs_diff = chk$abs_diff, pass = chk$pass)
    })
    #> GAMLSS-RS iteration 1: Global Deviance = 11375.33
    #> GAMLSS-RS iteration 2: Global Deviance = 11375.33
    #> GAMLSS-RS iteration 1: Global Deviance = 14782.83
    #> GAMLSS-RS iteration 2: Global Deviance = 14782.83
    #> GAMLSS-RS iteration 1: Global Deviance = 7267.968
    #> GAMLSS-RS iteration 2: Global Deviance = 7267.968
    #> GAMLSS-RS iteration 1: Global Deviance = 10699.55
    #> GAMLSS-RS iteration 2: Global Deviance = 10699.55
    #> GAMLSS-RS iteration 1: Global Deviance = 11694.15
    #> GAMLSS-RS iteration 2: Global Deviance = 11694.15
    #> GAMLSS-RS iteration 1: Global Deviance = 15982.17
    #> GAMLSS-RS iteration 2: Global Deviance = 15982.16
    #> GAMLSS-RS iteration 3: Global Deviance = 15982.16
    #> GAMLSS-RS iteration 1: Global Deviance = 18087.96
    #> GAMLSS-RS iteration 1: Global Deviance = -7154.868
    #> GAMLSS-RS iteration 2: Global Deviance = -7422.771
    #> GAMLSS-RS iteration 3: Global Deviance = -7422.823
    #> GAMLSS-RS iteration 4: Global Deviance = -7422.823
    summ <- do.call(rbind, Filter(Negate(is.null), summ))
    summ
    #>   family    ll_fast ll_generic abs_diff pass
    #> 1     NO  -5688.032  -5688.032        0 TRUE
    #> 2     PO -10568.077 -10568.077        0 TRUE
    #> 3  LOGNO  -4398.621  -4398.621        0 TRUE
    #> 4     GA  -8009.049  -8009.049        0 TRUE
    #> 5     IG  -8144.880  -8144.880        0 TRUE
    #> 6     LO  -7991.389  -7991.389        0 TRUE
    #> 7   GEOM  -9326.121  -9326.121        0 TRUE
    #> 8     BE   1678.217   1678.217        0 TRUE

## Wide family sweep (auto)

Below we attempt an automatic sweep across many families; those without installed densities or generators will be skipped gracefully.

    fams <- c("NO","PO","LOGNO","GA","IG","LO","LOGITNO","GEOM","BE",
              "NBI","NBII","LOGLOG","DEL","ZAGA","ZIP","ZINBI","DPO","GPO",
              "ZAIG","ZALG","BCT","BCPE","ZIPF","ZIPFmu","SICHEL","GLG",
              "BETA4","RS","WEI","GIG")
    n <- 3000
    res <- lapply(fams, function(fam) {
      y <- try(.gen_family(fam, n), silent = TRUE)
      if (inherits(y, "try-error") || is.null(y)) return(NULL)
      dat <- data.frame(y = y)
      fam_obj <- try(getFromNamespace(fam, "gamlss.dist")(), silent = TRUE)
      if (inherits(fam_obj, "try-error")) return(NULL)
      fit <- try(gamlss::gamlss(y ~ 1, data = dat, family = fam_obj), silent = TRUE)
      if (inherits(fit, "try-error")) return(NULL)
      chk <- check_fast_vs_generic(fit, dat, tol = 1e-6)
      data.frame(family = fam, abs_diff = chk$abs_diff, pass = chk$pass)
    })
    #> GAMLSS-RS iteration 1: Global Deviance = 8615.228
    #> GAMLSS-RS iteration 2: Global Deviance = 8615.228
    #> GAMLSS-RS iteration 1: Global Deviance = 10988.5
    #> GAMLSS-RS iteration 2: Global Deviance = 10988.5
    #> GAMLSS-RS iteration 1: Global Deviance = 5327.758
    #> GAMLSS-RS iteration 2: Global Deviance = 5327.758
    #> GAMLSS-RS iteration 1: Global Deviance = 7943.186
    #> GAMLSS-RS iteration 2: Global Deviance = 7943.186
    #> GAMLSS-RS iteration 1: Global Deviance = 8701.265
    #> GAMLSS-RS iteration 2: Global Deviance = 8701.265
    #> GAMLSS-RS iteration 1: Global Deviance = 11876.4
    #> GAMLSS-RS iteration 2: Global Deviance = 11876.4
    #> GAMLSS-RS iteration 3: Global Deviance = 11876.4
    #> GAMLSS-RS iteration 1: Global Deviance = 13655.01
    #> GAMLSS-RS iteration 1: Global Deviance = -5375.158
    #> GAMLSS-RS iteration 2: Global Deviance = -5578.084
    #> GAMLSS-RS iteration 3: Global Deviance = -5578.124
    #> GAMLSS-RS iteration 4: Global Deviance = -5578.124
    #> GAMLSS-RS iteration 1: Global Deviance = 11283.26
    #> GAMLSS-RS iteration 2: Global Deviance = 11283.26
    #> GAMLSS-RS iteration 1: Global Deviance = 11023
    #> GAMLSS-RS iteration 2: Global Deviance = 11023
    #> GAMLSS-RS iteration 3: Global Deviance = 11023
    #> GAMLSS-RS iteration 1: Global Deviance = 10670
    #> GAMLSS-RS iteration 2: Global Deviance = 10669.65
    #> GAMLSS-RS iteration 3: Global Deviance = 10669.34
    #> GAMLSS-RS iteration 4: Global Deviance = 10669.07
    #> GAMLSS-RS iteration 5: Global Deviance = 10668.83
    #> GAMLSS-RS iteration 6: Global Deviance = 10668.61
    #> GAMLSS-RS iteration 7: Global Deviance = 10668.42
    #> GAMLSS-RS iteration 8: Global Deviance = 10668.24
    #> GAMLSS-RS iteration 9: Global Deviance = 10668.09
    #> GAMLSS-RS iteration 10: Global Deviance = 10667.95
    #> GAMLSS-RS iteration 11: Global Deviance = 10667.82
    #> GAMLSS-RS iteration 12: Global Deviance = 10667.71
    #> GAMLSS-RS iteration 13: Global Deviance = 10667.6
    #> GAMLSS-RS iteration 14: Global Deviance = 10667.51
    #> GAMLSS-RS iteration 15: Global Deviance = 10667.43
    #> GAMLSS-RS iteration 16: Global Deviance = 10667.35
    #> GAMLSS-RS iteration 17: Global Deviance = 10667.28
    #> GAMLSS-RS iteration 18: Global Deviance = 10667.22
    #> GAMLSS-RS iteration 19: Global Deviance = 10667.17
    #> GAMLSS-RS iteration 20: Global Deviance = 10667.12
    #> Warning in RS(): Algorithm RS has not yet converged
    #> GAMLSS-RS iteration 1: Global Deviance = 9320.173
    #> GAMLSS-RS iteration 2: Global Deviance = 9320.173
    #> GAMLSS-RS iteration 1: Global Deviance = 10312.69
    #> GAMLSS-RS iteration 2: Global Deviance = 10311.55
    #> GAMLSS-RS iteration 3: Global Deviance = 10311.48
    #> GAMLSS-RS iteration 4: Global Deviance = 10311.44
    #> GAMLSS-RS iteration 5: Global Deviance = 10311.41
    #> GAMLSS-RS iteration 6: Global Deviance = 10311.4
    #> GAMLSS-RS iteration 7: Global Deviance = 10311.39
    #> GAMLSS-RS iteration 8: Global Deviance = 10311.38
    #> GAMLSS-RS iteration 9: Global Deviance = 10311.38
    #> GAMLSS-RS iteration 10: Global Deviance = 10311.38
    #> GAMLSS-RS iteration 11: Global Deviance = 10311.38
    #> GAMLSS-RS iteration 12: Global Deviance = 10311.38
    #> GAMLSS-RS iteration 1: Global Deviance = 11566.28
    #> GAMLSS-RS iteration 2: Global Deviance = 11566.18
    #> GAMLSS-RS iteration 3: Global Deviance = 11566.18
    #> GAMLSS-RS iteration 1: Global Deviance = 12274.44
    #> GAMLSS-RS iteration 2: Global Deviance = 12274.44
    #> GAMLSS-RS iteration 1: Global Deviance = 9841.625
    #> GAMLSS-RS iteration 2: Global Deviance = 9841.625
    #> GAMLSS-RS iteration 1: Global Deviance = 12231.44
    #> GAMLSS-RS iteration 2: Global Deviance = 12229.24
    #> GAMLSS-RS iteration 3: Global Deviance = 12228.23
    #> GAMLSS-RS iteration 4: Global Deviance = 12227.59
    #> GAMLSS-RS iteration 5: Global Deviance = 12227.14
    #> GAMLSS-RS iteration 6: Global Deviance = 12226.81
    #> GAMLSS-RS iteration 7: Global Deviance = 12226.55
    #> GAMLSS-RS iteration 8: Global Deviance = 12226.34
    #> GAMLSS-RS iteration 9: Global Deviance = 12226.17
    #> GAMLSS-RS iteration 10: Global Deviance = 12226.02
    #> GAMLSS-RS iteration 11: Global Deviance = 12225.9
    #> GAMLSS-RS iteration 12: Global Deviance = 12225.79
    #> GAMLSS-RS iteration 13: Global Deviance = 12225.7
    #> GAMLSS-RS iteration 14: Global Deviance = 12225.62
    #> GAMLSS-RS iteration 15: Global Deviance = 12225.56
    #> GAMLSS-RS iteration 16: Global Deviance = 12225.5
    #> GAMLSS-RS iteration 17: Global Deviance = 12225.44
    #> GAMLSS-RS iteration 18: Global Deviance = 12225.4
    #> GAMLSS-RS iteration 19: Global Deviance = 12225.35
    #> GAMLSS-RS iteration 20: Global Deviance = 12225.32
    #> Warning in RS(): Algorithm RS has not yet converged
    #> GAMLSS-RS iteration 1: Global Deviance = 10091.85
    #> GAMLSS-RS iteration 2: Global Deviance = 10091.37
    #> GAMLSS-RS iteration 3: Global Deviance = 10091.36
    #> GAMLSS-RS iteration 4: Global Deviance = 10091.36
    #> GAMLSS-RS iteration 1: Global Deviance = 9563.572
    #> GAMLSS-RS iteration 2: Global Deviance = 9505.614
    #> GAMLSS-RS iteration 3: Global Deviance = 9501.911
    #> GAMLSS-RS iteration 4: Global Deviance = 9501.197
    #> GAMLSS-RS iteration 5: Global Deviance = 9501.037
    #> GAMLSS-RS iteration 6: Global Deviance = 9500.992
    #> GAMLSS-RS iteration 7: Global Deviance = 9500.977
    #> GAMLSS-RS iteration 8: Global Deviance = 9500.971
    #> GAMLSS-RS iteration 9: Global Deviance = 9500.968
    #> GAMLSS-RS iteration 10: Global Deviance = 9500.967
    #> GAMLSS-RS iteration 11: Global Deviance = 9500.966
    res <- do.call(rbind, Filter(Negate(is.null), res))
    res
    #>    family abs_diff pass
    #> 1      NO        0 TRUE
    #> 2      PO        0 TRUE
    #> 3   LOGNO        0 TRUE
    #> 4      GA        0 TRUE
    #> 5      IG        0 TRUE
    #> 6      LO        0 TRUE
    #> 7    GEOM        0 TRUE
    #> 8      BE        0 TRUE
    #> 9     NBI        0 TRUE
    #> 10   NBII        0 TRUE
    #> 11    DEL        0 TRUE
    #> 12   ZAGA        0 TRUE
    #> 13  ZINBI        0 TRUE
    #> 14    DPO        0 TRUE
    #> 15    GPO        0 TRUE
    #> 16   ZAIG        0 TRUE
    #> 17 SICHEL        0 TRUE
    #> 18    WEI        0 TRUE
    #> 19    GIG        0 TRUE

### Wide family sweep with skip reasons

    fams <- c("NO","PO","LOGNO","GA","IG","LO","LOGITNO","GEOM","BE",
              "NBI","NBII","LOGLOG","DEL","ZAGA","ZIP","ZINBI","DPO","GPO",
              "ZAIG","ZALG","BCT","BCPE","ZIPF","ZIPFmu","SICHEL","GLG",
              "BETA4","RS","WEI","GIG")
    n <- 3000
    tols <- SelectBoost.gamlss:::.family_tolerance()
    tol_default <- tols[['.default']]
    rows <- lapply(fams, function(fam) {
      # try generator
      y <- try(.gen_family(fam, n), silent = TRUE)
      if (inherits(y, "try-error") || is.null(y)) {
        return(data.frame(family=fam, status="skip", reason="generator missing/failed", abs_diff=NA_real_, pass=NA))
      }
      dat <- data.frame(y = y)
      # try family object
      fam_obj <- try(getFromNamespace(fam, "gamlss.dist")(), silent = TRUE)
      if (inherits(fam_obj, "try-error")) {
        return(data.frame(family=fam, status="skip", reason="family constructor missing", abs_diff=NA_real_, pass=NA))
      }
      # try fit
      fit <- try(gamlss::gamlss(y ~ 1, data = dat, family = fam_obj), silent = TRUE)
      if (inherits(fit, "try-error")) {
        return(data.frame(family=fam, status="skip", reason="fit failed", abs_diff=NA_real_, pass=NA))
      }
      # evaluate
      tol_fam <- tols[[fam]] %||% tol_default
      chk <- check_fast_vs_generic(fit, dat, tol = tol_fam)
      data.frame(family=fam, status="ok", reason="", abs_diff=chk$abs_diff, pass=chk$pass)
    })
    #> GAMLSS-RS iteration 1: Global Deviance = 8484.742
    #> GAMLSS-RS iteration 2: Global Deviance = 8484.742
    #> GAMLSS-RS iteration 1: Global Deviance = 10872.98
    #> GAMLSS-RS iteration 2: Global Deviance = 10872.98
    #> GAMLSS-RS iteration 1: Global Deviance = 5341.986
    #> GAMLSS-RS iteration 2: Global Deviance = 5341.986
    #> GAMLSS-RS iteration 1: Global Deviance = 8015.778
    #> GAMLSS-RS iteration 2: Global Deviance = 8015.778
    #> GAMLSS-RS iteration 1: Global Deviance = 8692.182
    #> GAMLSS-RS iteration 2: Global Deviance = 8692.182
    #> GAMLSS-RS iteration 1: Global Deviance = 11909.62
    #> GAMLSS-RS iteration 2: Global Deviance = 11909.55
    #> GAMLSS-RS iteration 3: Global Deviance = 11909.55
    #> GAMLSS-RS iteration 1: Global Deviance = 13515
    #> GAMLSS-RS iteration 1: Global Deviance = -5382.726
    #> GAMLSS-RS iteration 2: Global Deviance = -5583.397
    #> GAMLSS-RS iteration 3: Global Deviance = -5583.435
    #> GAMLSS-RS iteration 4: Global Deviance = -5583.435
    #> GAMLSS-RS iteration 1: Global Deviance = 11308.87
    #> GAMLSS-RS iteration 2: Global Deviance = 11308.87
    #> GAMLSS-RS iteration 1: Global Deviance = 11075.33
    #> GAMLSS-RS iteration 2: Global Deviance = 11075.33
    #> GAMLSS-RS iteration 3: Global Deviance = 11075.33
    #> GAMLSS-RS iteration 1: Global Deviance = 10735.22
    #> GAMLSS-RS iteration 2: Global Deviance = 10735.04
    #> GAMLSS-RS iteration 3: Global Deviance = 10734.89
    #> GAMLSS-RS iteration 4: Global Deviance = 10734.76
    #> GAMLSS-RS iteration 5: Global Deviance = 10734.64
    #> GAMLSS-RS iteration 6: Global Deviance = 10734.54
    #> GAMLSS-RS iteration 7: Global Deviance = 10734.46
    #> GAMLSS-RS iteration 8: Global Deviance = 10734.38
    #> GAMLSS-RS iteration 9: Global Deviance = 10734.32
    #> GAMLSS-RS iteration 10: Global Deviance = 10734.27
    #> GAMLSS-RS iteration 11: Global Deviance = 10734.22
    #> GAMLSS-RS iteration 12: Global Deviance = 10734.19
    #> GAMLSS-RS iteration 13: Global Deviance = 10734.15
    #> GAMLSS-RS iteration 14: Global Deviance = 10734.13
    #> GAMLSS-RS iteration 15: Global Deviance = 10734.11
    #> GAMLSS-RS iteration 16: Global Deviance = 10734.09
    #> GAMLSS-RS iteration 17: Global Deviance = 10734.08
    #> GAMLSS-RS iteration 18: Global Deviance = 10734.08
    #> GAMLSS-RS iteration 19: Global Deviance = 10734.07
    #> GAMLSS-RS iteration 20: Global Deviance = 10734.07
    #> GAMLSS-RS iteration 1: Global Deviance = 9155.055
    #> GAMLSS-RS iteration 2: Global Deviance = 9155.055
    #> GAMLSS-RS iteration 1: Global Deviance = 10422.64
    #> GAMLSS-RS iteration 2: Global Deviance = 10421.36
    #> GAMLSS-RS iteration 3: Global Deviance = 10421.2
    #> GAMLSS-RS iteration 4: Global Deviance = 10421.1
    #> GAMLSS-RS iteration 5: Global Deviance = 10421.05
    #> GAMLSS-RS iteration 6: Global Deviance = 10421.01
    #> GAMLSS-RS iteration 7: Global Deviance = 10420.99
    #> GAMLSS-RS iteration 8: Global Deviance = 10420.98
    #> GAMLSS-RS iteration 9: Global Deviance = 10420.97
    #> GAMLSS-RS iteration 10: Global Deviance = 10420.97
    #> GAMLSS-RS iteration 11: Global Deviance = 10420.97
    #> GAMLSS-RS iteration 12: Global Deviance = 10420.96
    #> GAMLSS-RS iteration 13: Global Deviance = 10420.96
    #> GAMLSS-RS iteration 1: Global Deviance = 11345.71
    #> GAMLSS-RS iteration 2: Global Deviance = 11345.63
    #> GAMLSS-RS iteration 3: Global Deviance = 11345.63
    #> GAMLSS-RS iteration 1: Global Deviance = 12225.98
    #> GAMLSS-RS iteration 2: Global Deviance = 12225.98
    #> GAMLSS-RS iteration 1: Global Deviance = 9806.759
    #> GAMLSS-RS iteration 2: Global Deviance = 9806.759
    #> GAMLSS-RS iteration 1: Global Deviance = 12050.13
    #> GAMLSS-RS iteration 2: Global Deviance = 12049.42
    #> GAMLSS-RS iteration 3: Global Deviance = 12049.14
    #> GAMLSS-RS iteration 4: Global Deviance = 12048.99
    #> GAMLSS-RS iteration 5: Global Deviance = 12048.9
    #> GAMLSS-RS iteration 6: Global Deviance = 12048.84
    #> GAMLSS-RS iteration 7: Global Deviance = 12048.8
    #> GAMLSS-RS iteration 8: Global Deviance = 12048.77
    #> GAMLSS-RS iteration 9: Global Deviance = 12048.75
    #> GAMLSS-RS iteration 10: Global Deviance = 12048.74
    #> GAMLSS-RS iteration 11: Global Deviance = 12048.72
    #> GAMLSS-RS iteration 12: Global Deviance = 12048.71
    #> GAMLSS-RS iteration 13: Global Deviance = 12048.71
    #> GAMLSS-RS iteration 14: Global Deviance = 12048.7
    #> GAMLSS-RS iteration 15: Global Deviance = 12048.7
    #> GAMLSS-RS iteration 16: Global Deviance = 12048.69
    #> GAMLSS-RS iteration 17: Global Deviance = 12048.69
    #> GAMLSS-RS iteration 18: Global Deviance = 12048.69
    #> GAMLSS-RS iteration 19: Global Deviance = 12048.69
    #> GAMLSS-RS iteration 20: Global Deviance = 12048.68
    #> Warning in RS(): Algorithm RS has not yet converged
    #> GAMLSS-RS iteration 1: Global Deviance = 10251.6
    #> GAMLSS-RS iteration 2: Global Deviance = 10251.24
    #> GAMLSS-RS iteration 3: Global Deviance = 10251.24
    #> GAMLSS-RS iteration 4: Global Deviance = 10251.24
    #> GAMLSS-RS iteration 1: Global Deviance = 9539.068
    #> GAMLSS-RS iteration 2: Global Deviance = 9504.096
    #> GAMLSS-RS iteration 3: Global Deviance = 9502.578
    #> GAMLSS-RS iteration 4: Global Deviance = 9502.384
    #> GAMLSS-RS iteration 5: Global Deviance = 9502.352
    #> GAMLSS-RS iteration 6: Global Deviance = 9502.346
    #> GAMLSS-RS iteration 7: Global Deviance = 9502.344
    #> GAMLSS-RS iteration 8: Global Deviance = 9502.343
    res <- do.call(rbind, rows)
    res
    #>     family status                   reason abs_diff pass
    #> 1       NO     ok                                 0 TRUE
    #> 2       PO     ok                                 0 TRUE
    #> 3    LOGNO     ok                                 0 TRUE
    #> 4       GA     ok                                 0 TRUE
    #> 5       IG     ok                                 0 TRUE
    #> 6       LO     ok                                 0 TRUE
    #> 7  LOGITNO   skip               fit failed       NA   NA
    #> 8     GEOM     ok                                 0 TRUE
    #> 9       BE     ok                                 0 TRUE
    #> 10     NBI     ok                                 0 TRUE
    #> 11    NBII     ok                                 0 TRUE
    #> 12  LOGLOG   skip generator missing/failed       NA   NA
    #> 13     DEL     ok                                 0 TRUE
    #> 14    ZAGA     ok                                 0 TRUE
    #> 15     ZIP   skip generator missing/failed       NA   NA
    #> 16   ZINBI     ok                                 0 TRUE
    #> 17     DPO     ok                                 0 TRUE
    #> 18     GPO     ok                                 0 TRUE
    #> 19    ZAIG     ok                                 0 TRUE
    #> 20    ZALG   skip generator missing/failed       NA   NA
    #> 21     BCT   skip generator missing/failed       NA   NA
    #> 22    BCPE   skip generator missing/failed       NA   NA
    #> 23    ZIPF   skip generator missing/failed       NA   NA
    #> 24  ZIPFmu   skip generator missing/failed       NA   NA
    #> 25  SICHEL     ok                                 0 TRUE
    #> 26     GLG   skip generator missing/failed       NA   NA
    #> 27   BETA4   skip generator missing/failed       NA   NA
    #> 28      RS   skip generator missing/failed       NA   NA
    #> 29     WEI     ok                                 0 TRUE
    #> 30     GIG     ok                                 0 TRUE