analyse_baSAR() crashes after incomplete adaptation

[mcol]

This reports a number of errors then crashes:

data(ExampleData.BINfileData, envir = environment())
CWOSL.sub <- subset(CWOSL.SAR.Data,
                    subset = POSITION %in% c(1:3) & LTYPE == "OSL")
analyse_baSAR(CWOSL.sub, verbose = TRUE,
              source_doserate = c(0.04, 0.001),
              signal.integral = c(1:2),
              background.integral = c(80:100),
              method_control = list(n.chains = 1),
              n.MCMC = 10)
# NOTE: Stopping adaptation
# 
# 
# Error in ar.yw.default(x, aic = aic, order.max = order.max, na.action = na.action,  :
#   'order.max' must be >= 1
# In addition: Warning messages:
# 1: [analyse_baSAR()] Only multiple grain data provided, automatic selection skipped
# 2: In rjags::jags.model(file = textConnection(baSAR_models[[distribution]]),  :
#   Adaptation incomplete
# Error in ar.yw.default(x, aic = aic, order.max = order.max, na.action = na.action,  :
#   'order.max' must be >= 1
# Error in ar.yw.default(x, aic = aic, order.max = order.max, na.action = na.action,  :
#   'order.max' must be >= 1
# Error in ar.yw.default(x, aic = aic, order.max = order.max, na.action = na.action,  :
#   'order.max' must be >= 1
# Error in aliquot_quantiles[2, x] : subscript out of bounds

[mcol]

This is due to the combination of n.MCMC (which we set to 10) and the thin argument (which is set automatically also to 10 for problems of this size). If I set n.MCMC = 10 or method_control = list(thin = 5), we don't crash on aliquot_quantiles (but the errors from JAGS are still there, that only goes away for n.MCMC >= 2 * thin).

The problem happens in these lines: https://github.com/R-Lum/Luminescence/blob/2d12e99bf37a09cc1847d2f836961ab6270eee2b/R/analyse_baSAR.R#L2052-L2054 With n.MCMC = 10 and thin = 10 we only get one posterior sample for each of D[1], D[2], D[3], and these get put into a single column in plot.matrix, rather than in 3 different columns. By creating a matrix of the desired dimensions, the crash disappears.

[RLumSK]

Please set a minimum number for n.MC; this should solve the issue.