Description Usage Arguments Details See Also Examples
spfrontier.true.value
returns true parameter values for a simulation process
ezsimspfrontier
tests estimators of a spatial stochastic frontier model with different parameters
1 2 3 4 5 6 7 8 9 | spfrontier.true.value()
ezsimspfrontier(
runs,
params,
inefficiency = "half-normal",
logging = "info",
control = list()
)
|
runs |
a number of simulated samples |
params |
a set with parameters to be used in simulation. |
inefficiency |
sets the distribution for inefficiency error component. Possible values are 'half-normal' (for half-normal distribution) and 'truncated' (for truncated normal distribution). By default set to 'half-normal'. See references for explanations |
logging |
an optional level of logging. Possible values are 'quiet','warn','info','debug'. By default set to quiet. |
control |
an optional list of control parameters for simulation process. Currently the procedure supports: |
The spfrontier.true.value
function should notbe used directly, it is exported for supporting ezsim
The ezsimspfrontier
function executes multiple calls of the spfrontier
estimator on a simulated data set,
generated on the base of provided parameters. The resulting estimates can be analysed for biasedness, efficiency, etc.
1 2 3 4 5 6 7 8 9 10 11 |
Loading required package: moments
Loading required package: tmvtnorm
Loading required package: mvtnorm
Loading required package: Matrix
Loading required package: stats4
Loading required package: gmm
Loading required package: sandwich
Loading required package: spdep
Loading required package: sp
Attaching package: 'spdep'
The following object is masked from 'package:moments':
geary
Loading required package: ezsim
Thank you for using 'spfrontier'
sh: 1: wc: Permission denied
sh: 1: cannot create /dev/null: Permission denied
Predefined random seed: 999
[1] "Mark = 270"
Start [pid= 14445 n = 50 , run = 1 ]-------------------------> -2.17513749937688
Log-likelihood (true DGP) (pid=14445) = -85.2578166841441
INFO spfrontier (pid=14445) Estimator started
INFO spfrontier (pid=14445) Calculating initial values
INFO calculateInitialValues (pid=14445) Initial values method errorsarlm
INFO spfrontier (pid=14445) Initial values:
Beta1 Beta2 Beta3 sigmaV sigmaU
1.6063826 10.3300718 1.6485546 0.5442064 2.1509508
Maximizing -- use negfn and neggr
INFO doTryCatch (pid=14445) Calculating numeric hessian, number of required function calls is 122 ...
INFO optimEstimator (pid=14445) Convergence is achieved [ 0 ]
INFO optimEstimator (pid=14445) Log-Likelihood value = -79.6629105970691
INFO spfrontier (pid=14445) Completed, status = 0
INFO spfrontier (pid=14445) Final estimates:
Beta1 Beta2 Beta3 sigmaV sigmaU
4.12618894 9.76250494 1.79765749 0.01497415 2.30051601
<-------------------------End pid= 14445
[1] "Mark = 92"
Start [pid= 14445 n = 50 , run = 2 ]-------------------------> -2.28343333422972
Log-likelihood (true DGP) (pid=14445) = -91.6509080951936
INFO spfrontier (pid=14445) Estimator started
INFO spfrontier (pid=14445) Calculating initial values
INFO calculateInitialValues (pid=14445) Initial values method errorsarlm
INFO spfrontier (pid=14445) Initial values:
Beta1 Beta2 Beta3 sigmaV sigmaU
1.5288196 10.6390541 1.2509212 0.8359614 2.0947003
Maximizing -- use negfn and neggr
INFO doTryCatch (pid=14445) Calculating numeric hessian, number of required function calls is 122 ...
INFO optimEstimator (pid=14445) Convergence is achieved [ 0 ]
INFO optimEstimator (pid=14445) Log-Likelihood value = -89.0243943935539
INFO spfrontier (pid=14445) Completed, status = 0
INFO spfrontier (pid=14445) Final estimates:
Beta1 Beta2 Beta3 sigmaV sigmaU
3.8235779 10.5126460 1.1278940 0.5276554 2.3985818
<-------------------------End pid= 14445
[1] "Mark = 48"
Start [pid= 14445 n = 100 , run = 1 ]-------------------------> -1.48369329781614
Log-likelihood (true DGP) (pid=14445) = -176.176710777771
INFO spfrontier (pid=14445) Estimator started
INFO spfrontier (pid=14445) Calculating initial values
INFO calculateInitialValues (pid=14445) Initial values method errorsarlm
INFO spfrontier (pid=14445) Initial values:
Beta1 Beta2 Beta3 sigmaV sigmaU
3.3819685 9.9766585 0.7863375 0.5846982 2.3548633
Maximizing -- use negfn and neggr
INFO doTryCatch (pid=14445) Calculating numeric hessian, number of required function calls is 122 ...
INFO optimEstimator (pid=14445) Convergence is achieved [ 0 ]
INFO optimEstimator (pid=14445) Log-Likelihood value = -175.449286035879
INFO spfrontier (pid=14445) Completed, status = 0
INFO spfrontier (pid=14445) Final estimates:
Beta1 Beta2 Beta3 sigmaV sigmaU
5.2352487 9.8724719 0.9337123 0.4388289 2.4202759
<-------------------------End pid= 14445
[1] "Mark = 35"
Start [pid= 14445 n = 100 , run = 2 ]-------------------------> 1.09278181091677
Log-likelihood (true DGP) (pid=14445) = -170.783923945398
INFO spfrontier (pid=14445) Estimator started
INFO spfrontier (pid=14445) Calculating initial values
INFO calculateInitialValues (pid=14445) Initial values method errorsarlm
INFO spfrontier (pid=14445) Initial values:
Beta1 Beta2 Beta3 sigmaV sigmaU
3.1537994 9.9032982 1.2046796 0.3065791 2.2342946
Maximizing -- use negfn and neggr
INFO doTryCatch (pid=14445) Calculating numeric hessian, number of required function calls is 122 ...
INFO optimEstimator (pid=14445) Convergence is achieved [ 0 ]
INFO optimEstimator (pid=14445) Log-Likelihood value = -168.399327906323
INFO spfrontier (pid=14445) Completed, status = 0
INFO spfrontier (pid=14445) Final estimates:
Beta1 Beta2 Beta3 sigmaV sigmaU
4.9751404 9.9602544 1.0262273 0.5830375 2.0664144
<-------------------------End pid= 14445
Executed in 3.24929308891296
estimator n beta0 beta1 beta2 sigmaV sigmaU Mean TV Bias SD
1 beta[0] 50 5 10 1 0.5 2.5 3.9749 5.0 -1.0251 0.2140
2 beta[0] 100 5 10 1 0.5 2.5 5.1052 5.0 0.1052 0.1839
3 beta[1] 50 5 10 1 0.5 2.5 10.1376 10.0 0.1376 0.5304
4 beta[1] 100 5 10 1 0.5 2.5 9.9164 10.0 -0.0836 0.0621
5 beta[2] 50 5 10 1 0.5 2.5 1.4628 1.0 0.4628 0.4736
6 beta[2] 100 5 10 1 0.5 2.5 0.9800 1.0 -0.0200 0.0654
7 sigma[v] 50 5 10 1 0.5 2.5 0.2713 0.5 -0.2287 0.3625
8 sigma[v] 100 5 10 1 0.5 2.5 0.5109 0.5 0.0109 0.1020
9 sigma[u] 50 5 10 1 0.5 2.5 2.3495 2.5 -0.1505 0.0693
10 sigma[u] 100 5 10 1 0.5 2.5 2.2433 2.5 -0.2567 0.2502
rmse BiasPercentage
1 1.0472 -0.2050
2 0.2119 0.0210
3 0.5480 0.0138
4 0.1042 -0.0084
5 0.6622 0.4628
6 0.0684 -0.0200
7 0.4286 -0.4574
8 0.1026 0.0219
9 0.1657 -0.0602
10 0.3584 -0.1027
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