| /dports/math/py-arviz/arviz-0.11.4/arviz/tests/base_tests/ |
| H A D | test_diagnostics.py | 13 from ...stats import bfmi, ess, mcse, rhat
142 "mcse_mean": lambda x: mcse(x, method="mean"),
143 "mcse_sd": lambda x: mcse(x, method="sd"),
144 "mcse_median": lambda x: mcse(x, method="median"),
377 mcse(np.random.randn(2, 300, 10))
401 mcse_hat = mcse(data, method=mcse_method, prob=0.34)
403 mcse_hat = mcse(data, method=mcse_method)
409 mcse_hat = mcse(data, method=mcse_method)
415 mcse(data, method=method, prob=None)
426 mcse_mean_hat = mcse(ary, method="mean")
[all …]
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| H A D | test_diagnostics_numba.py | 10 from ...stats import bfmi, mcse, rhat
61 non_numba = mcse(school, method=method, prob=prob)
63 with_numba = mcse(school, method=method, prob=prob)
|
| /dports/math/py-arviz/arviz-0.11.4/arviz/plots/ |
| H A D | mcseplot.py | 8 from ..stats import mcse
136 [mcse(data, var_names=var_names, method="quantile", prob=p) for p in probs], dim="mcse_dim"
147 mean_mcse = mcse(data, var_names=var_names, method="mean")
148 sd_mcse = mcse(data, var_names=var_names, method="sd")
|
| /dports/math/py-spvcm/spvcm-0.3.0/spvcm/tests/ |
| H A D | make_data.py | 4 from spvcm.diagnostics import psrf, mcse, hpd_interval, effective_size, geweke
30 known_mcse = mcse(model, varnames=['Tau2'], method=method)
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| H A D | test_diagnostics.py | 4 from spvcm.diagnostics import psrf, geweke, effective_size, hpd_interval, summarize, mcse
142 multi_ses = mcse(trace=self.trace, varnames=['Tau2'], method=method)
143 single_ses = mcse(trace=self.single_trace, varnames=['Tau2'], method=method)
148 _ =mcse(trace=self.single_trace, varnames=['Tau2'], rescale=3)
|
| /dports/math/R-cran-mcmc/mcmc/tests/ |
| H A D | temp-ser-witch.Rout.save | 114 > mu.mcse.rel <- apply(mu.batch.rel, 2, sd) / sqrt(out$nbatch)
115 > mu.mcse.rel
118 > foo <- cbind(mu, mu * mu.mcse.rel)
|
| /dports/finance/odoo/odoo-19d77c2a03335eb95a686bd69a1b56b38e87d609/doc/cla/individual/ |
| H A D | stanisljevic.md | 11 Sasa Stanisljevic mcse.sasa@gmail.com https://github.com/stanisljevic
|
| /dports/science/py-chempy/chempy-0.8.2/joss-paper/ |
| H A D | paper.bib | 43 doi = {10.1109/mcse.2011.37},
44 url = {https://doi.org/10.1109/mcse.2011.37},
|
| /dports/math/R-cran-mcmc/mcmc/vignettes/ |
| H A D | demo.Rnw | 303 <<label=metropolis-mcse-mu>>=
305 mu.mcse
357 sigmasq.mcse
380 <<label=metropolis-mcse-sigma>>=
382 sigma.mcse <- sigmasq.mcse / (2 * sigma)
384 sigma.mcse
397 <<metropolis-mcse-mu>>
398 <<metropolis-mcse-sigmasq>>
399 <<metropolis-mcse-sigma>>
409 foo <- rbind(mu, mu.mcse)
[all …]
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| H A D | bfst.Rnw | 652 mcse.log.10.bayes <- (1 / log(10)) * sqrt(diag(fred) / sally^2 -
655 mcse.log.10.bayes
657 foompter <- cbind(models, log.10.bayes, mcse.log.10.bayes)
672 mcse.log.10.bayes.too <- (1 / log(10)) *
674 all.equal(mcse.log.10.bayes, mcse.log.10.bayes.too)
|
| /dports/math/R-cran-mcmc/mcmc/inst/doc/ |
| H A D | demo.Rnw | 303 <<label=metropolis-mcse-mu>>=
305 mu.mcse
357 sigmasq.mcse
380 <<label=metropolis-mcse-sigma>>=
382 sigma.mcse <- sigmasq.mcse / (2 * sigma)
384 sigma.mcse
397 <<metropolis-mcse-mu>>
398 <<metropolis-mcse-sigmasq>>
399 <<metropolis-mcse-sigma>>
409 foo <- rbind(mu, mu.mcse)
[all …]
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| H A D | bfst.Rnw | 652 mcse.log.10.bayes <- (1 / log(10)) * sqrt(diag(fred) / sally^2 -
655 mcse.log.10.bayes
657 foompter <- cbind(models, log.10.bayes, mcse.log.10.bayes)
672 mcse.log.10.bayes.too <- (1 / log(10)) *
674 all.equal(mcse.log.10.bayes, mcse.log.10.bayes.too)
|
| /dports/ftp/tnftp/tnftp-20210827/src/ |
| H A D | ftp.c | 1813 int mcse; in pswitch() member
1863 ip->mcse = mcase; in pswitch()
1864 mcase = op->mcse; in pswitch()
|
| /dports/math/py-spvcm/spvcm-0.3.0/spvcm/ |
| H A D | plotting.py | 325 diags = [list(diag.mcse(chain=np.hstack(splits[:i+1])).values())[0] for i in range(N_bins)]
|
| H A D | diagnostics.py | 535 def mcse(model = None, trace=None, chain = None, varnames = None, function
|
| /dports/security/krb5-appl/krb5-appl-1.0.3/gssftp/ftp/ |
| H A D | ftp.c | 1609 int mcse; in pswitch() member
1664 ip->mcse = mcase; in pswitch()
1665 mcase = op->mcse; in pswitch()
|
| /dports/ftp/bsdftpd-ssl/bsdftpd-ssl-1.1.0/ftp/ |
| H A D | ftp.c | 2049 int mcse; member
2113 ip->mcse = mcase;
2114 mcase = op->mcse;
|
| /dports/math/py-arviz/arviz-0.11.4/arviz/stats/ |
| H A D | diagnostics.py | 325 def mcse(data, *, var_names=None, method="mean", prob=None, dask_kwargs=None): function
|
| /dports/comms/kermit/kermit-9.0.305.04/ |
| H A D | ckcftp.c | 13562 int mcse; member
13622 ip->mcse = mcase;
13623 mcase = op->mcse;
|
| /dports/security/ncrack/ncrack-0.7/lists/ |
| H A D | phpbb.pwd | 3051 mcse
|
| /dports/math/py-spvcm/spvcm-0.3.0/spvcm/examples/ |
| H A D | using_the_sampler.ipynb | 1720 …"We can also compute Monte Carlo Standard Errors like in the `mcse` R package, which represent the…
1742 "spvcm.diagnostics.mcse(vcsma, varnames=['Tau2', 'Sigma2'])"
|
| /dports/chinese/wenju/wenju-1.6/src/tim/tables/ |
| H A D | liu.tim | 11134 mcse=翷
|
| /dports/security/dirbuster/DirBuster-1.0-RC1/ |
| H A D | directories.jbrofuzz | 31375 mcse
|
| /dports/net/ndpi/nDPI-92a1be2/tests/dga/ |
| H A D | test_non_dga.csv | 17891 mcse.hu
|
| /dports/editors/mined/mined-2015.25/src/ |
| H A D | keymaps.t | 64315 "mcse\000翷\000"
|