thin_dt

post-hoc thinning of MCMC chains which have been converted to a data.table

thin_dt(dt, thin = 1)

Arguments

dt	an object of class "data.table" returned from `mcmc_to_dt`
thin	thinning interval

Value

a data.table dataframe

Examples

library(coda)
data(line)
mcmc_dt <- mcmc_to_dt(line)
thin_dt(mcmc_dt, thin = 10)
#>      iteration chain parameter    value
#>   1:         1     1     alpha 7.173130
#>   2:        11     1     alpha 3.065240
#>   3:        21     1     alpha 2.876460
#>   4:        31     1     alpha 2.943310
#>   5:        41     1     alpha 3.087570
#>  ---                                   
#> 116:       151     2     sigma 0.764629
#> 117:       161     2     sigma 1.315890
#> 118:       171     2     sigma 1.034110
#> 119:       181     2     sigma 2.362830
#> 120:       191     2     sigma 1.009290
thin_dt(mcmc_dt, thin = 2)
#>      iteration chain parameter    value
#>   1:         1     1     alpha 7.173130
#>   2:         3     1     alpha 3.669890
#>   3:         5     1     alpha 3.705440
#>   4:         7     1     alpha 2.702060
#>   5:         9     1     alpha 3.534060
#>  ---                                   
#> 596:       191     2     sigma 1.009290
#> 597:       193     2     sigma 2.249060
#> 598:       195     2     sigma 0.606293
#> 599:       197     2     sigma 0.846828
#> 600:       199     2     sigma 0.672417
thin_dt(mcmc_dt, thin = 20)
#>     iteration chain parameter     value
#>  1:         1     1     alpha  7.173130
#>  2:        21     1     alpha  2.876460
#>  3:        41     1     alpha  3.087570
#>  4:        61     1     alpha  2.994820
#>  5:        81     1     alpha  2.212900
#>  6:       101     1     alpha  3.524700
#>  7:       121     1     alpha  3.338330
#>  8:       141     1     alpha  2.807910
#>  9:       161     1     alpha  3.169770
#> 10:       181     1     alpha  3.233470
#> 11:         1     1      beta -1.566200
#> 12:        21     1      beta  1.028060
#> 13:        41     1      beta  0.674701
#> 14:        61     1      beta  0.876193
#> 15:        81     1      beta  0.770004
#> 16:       101     1      beta  0.753859
#> 17:       121     1      beta  0.659257
#> 18:       141     1      beta  1.154520
#> 19:       161     1      beta  0.858167
#> 20:       181     1      beta  0.934646
#> 21:         1     1     sigma 11.233100
#> 22:        21     1     sigma  0.582580
#> 23:        41     1     sigma  0.840521
#> 24:        61     1     sigma  0.493587
#> 25:        81     1     sigma  1.387510
#> 26:       101     1     sigma  0.734966
#> 27:       121     1     sigma  1.260040
#> 28:       141     1     sigma  0.637226
#> 29:       161     1     sigma  0.806075
#> 30:       181     1     sigma  0.618407
#> 31:         1     2     alpha  2.066500
#> 32:        21     2     alpha  3.348630
#> 33:        41     2     alpha  3.110930
#> 34:        61     2     alpha  3.571770
#> 35:        81     2     alpha  3.158990
#> 36:       101     2     alpha  3.074090
#> 37:       121     2     alpha  1.698710
#> 38:       141     2     alpha  3.060500
#> 39:       161     2     alpha  2.732490
#> 40:       181     2     alpha  3.103140
#> 41:         1     2      beta  0.949830
#> 42:        21     2      beta  0.466017
#> 43:        41     2      beta  0.951993
#> 44:        61     2      beta  0.414160
#> 45:        81     2      beta  0.526451
#> 46:       101     2      beta  0.863503
#> 47:       121     2      beta  0.429794
#> 48:       141     2      beta  1.083460
#> 49:       161     2      beta  1.469440
#> 50:       181     2      beta -0.423911
#> 51:         1     2     sigma  2.853790
#> 52:        21     2     sigma  0.697648
#> 53:        41     2     sigma  1.157920
#> 54:        61     2     sigma  0.880437
#> 55:        81     2     sigma  0.661277
#> 56:       101     2     sigma  0.642839
#> 57:       121     2     sigma  1.288570
#> 58:       141     2     sigma  1.417590
#> 59:       161     2     sigma  1.315890
#> 60:       181     2     sigma  2.362830
#>     iteration chain parameter     value