Error in { : task 28 failed - "non-conformable arrays" #1
Comments
|
Thanks for reporting this. Any chance you could provide a reproducible example of this? |
|
Hi Jonas, Thanks for your replay and package. I attached my code and data. |
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System: Macbook M2Max 96GB
R: 4.4.1
mnet: 0.14
data: data.table all vars are num
`
zVars <- c("WeChat",
"XiaoHongShu",
"HonorofKings","PUBG",
"Douyin",
"Taobao","PDD",
"Desktop",
"Novel",
"Education")
zData_summary2
str(zData_summary2)
Classes ‘data.table’ and 'data.frame': 9669 obs. of 14 variables:
$ id : num 5 5 5 5 5 5 5 5 5 5 ...
$ hou : num 0 0 0 0 1 1 1 5 5 6 ...
$ quarter : num 0 1 2 3 0 1 2 2 3 0 ...
$ group : num 1 1 1 1 1 1 1 1 1 1 ...
$ WeChat : num 0.1 0 0 0 0 ...
$ XiaoHongShu : num 0 0 0 0 0 0 0 0 0 0 ...
$ HonorofKings: num 0 0 0 0 0 0 0 0 0 0 ...
$ PUBG : num 0 0 0 0 0 0 0 0 0 0 ...
$ Douyin : num 0 0 0 0 0 0 0 0 0 0 ...
$ Taobao : num 0 0 0 0 0 0 0 0 0 0 ...
$ PDD : num 0 0 0 0 0 0 0 0 0 0 ...
$ Desktop : num 1 1 1 1 1 1 1 1 1 1 ...
$ Novel : num 0 0 0 0 0 0 0 0 0 0 ...
$ Education : num 0 0 0 0 0 0 0 0 0 0 ...
`
output <- mlVAR_GC(data = zData_summary2,
starting worker pid=57437 on localhost:11240 at 20:56:15.442
starting worker pid=57450 on localhost:11240 at 20:56:15.590
starting worker pid=57471 on localhost:11240 at 20:56:15.725
starting worker pid=57484 on localhost:11240 at 20:56:15.892
starting worker pid=57497 on localhost:11240 at 20:56:16.030
starting worker pid=57510 on localhost:11240 at 20:56:16.197
starting worker pid=57523 on localhost:11240 at 20:56:16.352
starting worker pid=57536 on localhost:11240 at 20:56:16.511
starting worker pid=57549 on localhost:11240 at 20:56:16.659
starting worker pid=57562 on localhost:11240 at 20:56:16.814
starting worker pid=57575 on localhost:11240 at 20:56:17.018
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
|======================================================================================================================================================================================= | 95%Warning message:
In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning messages:
1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning messages:
2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning message:
1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning messages:
2: 1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning messages:
Warning messages:
1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning message:
In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning messages:
1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning message:
In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning messages:
1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
Warning messages:
1: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
2: In mlVAR(data = l_data_h0[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
|================================================================================================================================================================================================| 100%Warning messages:
1: In e$fun(obj, substitute(ex), parent.frame(), e$data) :
already exporting variable(s): m_data_cmb, vars, idvar, estimator, contemporaneous, temporal, totalN, v_Ns, v_ids, pb, pbar, dayvar, beepvar, paired
2: In mlVAR(data = l_data[[j]], vars = vars, idvar = idvar, estimator = estimator, :
1 subjects detected with < 20 measurements. This is not recommended, as within-person centering with too few observations per subject will lead to biased estimates (most notably: negative self-loops).
starting worker pid=64196 on localhost:11240 at 21:23:38.042
starting worker pid=64209 on localhost:11240 at 21:23:38.177
starting worker pid=64222 on localhost:11240 at 21:23:38.321
starting worker pid=64235 on localhost:11240 at 21:23:38.449
starting worker pid=64257 on localhost:11240 at 21:23:38.606
starting worker pid=64270 on localhost:11240 at 21:23:38.748
starting worker pid=64284 on localhost:11240 at 21:23:38.890
starting worker pid=64297 on localhost:11240 at 21:23:39.050
starting worker pid=64310 on localhost:11240 at 21:23:39.214
starting worker pid=64323 on localhost:11240 at 21:23:39.375
starting worker pid=64336 on localhost:11240 at 21:23:39.554
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
Loading required package: mnet
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
This is mnet 0.1.4
Please report issues on Github: https://github.com/jmbh/mnet/issues
loaded mnet and set parent environment
|============================================================================================================================================================================================== | 99%Error in { : task 28 failed - "non-conformable arrays"
In addition: Warning message:
In e$fun(obj, substitute(ex), parent.frame(), e$data) :
already exporting variable(s): m_data_cmb, vars, idvar, estimator, contemporaneous, temporal, totalN, v_Ns, v_ids, pb, pbar, dayvar, beepvar, paired
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