| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/statespace/tests/results/ |
| H A D | results_sarimax_coverage.csv | 2 "arima wpi, arima(3,0,0) noconstant vce(oim)",-145.917,"1.600047,-.3624836,-.2377553,.7515501"
3 "arima wpi c, arima(3,0,0) noconstant vce(oim)",-145.1327,"78.60683,1.599097,-.3606729,-.2392393,.7…
4 "arima wpi c t, arima(3,0,0) noconstant vce(oim)",-139.5423,"19.46176,.768438,1.528349,-.3448674,-.…
6 "arima wpi, arima(3,2,0) noconstant vce(oim)",-135.9354,"-.4536069,-.3408174,-.0977653,.7363397"
8 "arima wpi, arima(3,0,0) noconstant vce(oim) diffuse",-159.3091,"1.641477,-.6359852,-.0014474,.7450…
9 "arima wpi x, arima(3,0,0) noconstant vce(oim)",-145.7514,".0806147,1.610143,-.382758,-.2275756,.75…
10 "arima wpi, arima(0,0,3) noconstant vce(oim)",-540.8154,"-505.7114,-970.6211,-507.9258,.0357879"
11 "arima wpi c, arima(0,0,3) noconstant vce(oim)",-379.8598,"62.99608,2.451664,2.39358,.8955524,4.920…
14 "arima wpi, arima(0,2,3) noconstant vce(oim)",-136.14,"-.4584812,-.1298735,.0632101,.7375874"
16 "arima wpi, arima(0,0,3) noconstant vce(oim) diffuse",-587.4832,"-27.57705,-55.33257,-29.37171,.645…
[all …]
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| H A D | test_sarimax_coverage.do | 44 capture arima wpi, arima(3,0,0) noconstant vce(oim)
50 capture arima wpi c, arima(3,0,0) noconstant vce(oim)
54 capture arima wpi c t, arima(3,0,0) noconstant vce(oim)
58 capture arima wpi c t3, arima(3,0,0) noconstant vce(oim)
62 capture arima wpi, arima(3,2,0) noconstant vce(oim)
74 capture arima wpi x, arima(3,0,0) noconstant vce(oim)
78 capture arima wpi, arima(0,0,3) noconstant vce(oim)
84 capture arima wpi c, arima(0,0,3) noconstant vce(oim)
96 capture arima wpi, arima(0,2,3) noconstant vce(oim)
113 capture arima wpi, arima(3,0,3) noconstant vce(oim)
[all …]
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| H A D | test_sarimax_stata.do | 3 arima wpi, arima(1,1,1) vce(opg)
4 arima wpi, arima(1,1,1) vce(oim)
5 arima wpi, arima(1,1,1) vce(robust)
6 arima wpi, arima(1,1,1) diffuse vce(opg)
7 arima wpi, arima(1,1,1) diffuse vce(oim)
24 arima D.ln_wpi, ar(1) ma(1 4) vce(opg)
25 arima D.ln_wpi, ar(1) ma(1 4) vce(oim)
30 arima lnair, arima(0,1,1) sarima(0,1,1,12) noconstant vce(opg)
31 arima lnair, arima(0,1,1) sarima(0,1,1,12) noconstant vce(oim)
41 arima consump m2 if tin(, 1978q1), ar(1) ma(1)
[all …]
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| /dports/math/R/R-4.1.2/src/library/stats/tests/ |
| H A D | ts-tests.R | 47 (fit1 <- arima(presidents, c(1, 0, 0)))
68 arima(tmp, order=c(2,0,0), xreg=trend)
69 arima(tmp, order=c(1,1,1), xreg=trend)
71 arima(tmp, order=c(2,0,0), xreg=trend)
74 predict(arima(lh, order=c(1,0,1)), n.ahead=5)
75 predict(arima(lh, order=c(1,1,0)), n.ahead=5)
76 predict(arima(lh, order=c(0,2,1)), n.ahead=5)
79 arima(lh, order = c(1,0,1), init = c(0.5, 0.5, NA))
80 arima(lh, order = c(1,0,1), init = c(0.5, 2, NA))
86 arima(LakeHuron, order=c(2,0,0), xreg=trend)
[all …]
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| /dports/math/libRmath/R-4.1.1/src/library/stats/tests/ |
| H A D | ts-tests.R | 47 (fit1 <- arima(presidents, c(1, 0, 0)))
68 arima(tmp, order=c(2,0,0), xreg=trend)
69 arima(tmp, order=c(1,1,1), xreg=trend)
71 arima(tmp, order=c(2,0,0), xreg=trend)
74 predict(arima(lh, order=c(1,0,1)), n.ahead=5)
75 predict(arima(lh, order=c(1,1,0)), n.ahead=5)
76 predict(arima(lh, order=c(0,2,1)), n.ahead=5)
79 arima(lh, order = c(1,0,1), init = c(0.5, 0.5, NA))
80 arima(lh, order = c(1,0,1), init = c(0.5, 2, NA))
86 arima(LakeHuron, order=c(2,0,0), xreg=trend)
[all …]
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| /dports/math/gretl/gretl-2021d/share/scripts/misc/ |
| H A D | bjg.inp | 5 arima 0 1 1 ; 0 1 1 ; lg --nc --conditional
7 arima 0 1 1 ; 0 1 1 ; lg --nc --x-12-arima --conditional
9 arima 0 1 1 ; 0 1 1 ; lg --nc
11 arima 0 1 1 ; 0 1 1 ; lg --nc --x-12-arima
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| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/tests/results/ |
| H A D | arma_forecast.inp | 7 arima 1 0 1 ; 1 --nc
11 arima 4 0 1 ; 3 --nc
15 arima 5 0 0 ; 5 --nc
19 arima 1 0 1 ; 7
23 arima 4 0 1 ; 9
27 arima 5 0 0 ; 11
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| H A D | arima_forecast.inp | 6 arima 1 1 1 ; cpi --nc
10 arima 1 1 1 ; cpi
16 arima 2 1 1 ; cpi --nc
20 arima 2 1 1 ; cpi
|
| H A D | arima.R | 6 mod111 <- arima(cpi, order=c(1,1,1), method="CSS")
11 mod111 <- arima(dcpi, order=c(1,0,1), method="CSS")
17 mod112 <- arima(dcpi, order=c(1,0,2), method="CSS", init=c(-0.692425, 1.07366, 0.172024, 0.905322))
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| /dports/math/R/R-4.1.2/src/library/stats/man/ |
| H A D | arima.sim.Rd | 1 % File src/library/stats/man/arima.sim.Rd
6 \name{arima.sim}
7 \alias{arima.sim}
14 arima.sim(model, n, rand.gen = rnorm, innov = rand.gen(n, \dots),
39 See \code{\link{arima}} for the precise definition of an ARIMA model.
44 \code{model}, in the same way as for \code{\link{arima}}. Other
57 \code{\link{arima}}
62 arima.sim(n = 63, list(ar = c(0.8897, -0.4858), ma = c(-0.2279, 0.2488)),
65 arima.sim(n = 63, list(ar = c(0.8897, -0.4858), ma = c(-0.2279, 0.2488)),
69 ts.sim <- arima.sim(list(order = c(1,1,0), ar = 0.7), n = 200)
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| H A D | predict.arima.Rd | 1 % File src/library/stats/man/predict.arima.Rd
10 Forecast from models fitted by \code{\link{arima}}.
17 \item{object}{The result of an \code{arima} fit.}
57 \code{\link{arima}}
62 predict(arima(lh, order = c(3,0,0)), n.ahead = 12)
64 (fit <- arima(USAccDeaths, order = c(0,1,1),
|
| H A D | arima.Rd | 1 % File src/library/stats/man/arima.Rd
6 \name{arima}
7 \alias{arima}
14 arima(x, order = c(0L, 0L, 0L),
256 arima(lh, order = c(1,0,0))
257 arima(lh, order = c(3,0,0))
258 arima(lh, order = c(1,0,1))
260 arima(lh, order = c(3,0,0), method = "CSS")
272 (fit1 <- arima(presidents, c(1, 0, 0)))
279 AIC(fit1, arima(presidents, c(2,0,0)),
[all …]
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| /dports/math/libRmath/R-4.1.1/src/library/stats/man/ |
| H A D | arima.sim.Rd | 1 % File src/library/stats/man/arima.sim.Rd
6 \name{arima.sim}
7 \alias{arima.sim}
14 arima.sim(model, n, rand.gen = rnorm, innov = rand.gen(n, \dots),
39 See \code{\link{arima}} for the precise definition of an ARIMA model.
44 \code{model}, in the same way as for \code{\link{arima}}. Other
57 \code{\link{arima}}
62 arima.sim(n = 63, list(ar = c(0.8897, -0.4858), ma = c(-0.2279, 0.2488)),
65 arima.sim(n = 63, list(ar = c(0.8897, -0.4858), ma = c(-0.2279, 0.2488)),
69 ts.sim <- arima.sim(list(order = c(1,1,0), ar = 0.7), n = 200)
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| H A D | predict.arima.Rd | 1 % File src/library/stats/man/predict.arima.Rd
10 Forecast from models fitted by \code{\link{arima}}.
17 \item{object}{The result of an \code{arima} fit.}
57 \code{\link{arima}}
62 predict(arima(lh, order = c(3,0,0)), n.ahead = 12)
64 (fit <- arima(USAccDeaths, order = c(0,1,1),
|
| H A D | arima.Rd | 1 % File src/library/stats/man/arima.Rd
6 \name{arima}
7 \alias{arima}
14 arima(x, order = c(0L, 0L, 0L),
256 arima(lh, order = c(1,0,0))
257 arima(lh, order = c(3,0,0))
258 arima(lh, order = c(1,0,1))
260 arima(lh, order = c(3,0,0), method = "CSS")
272 (fit1 <- arima(presidents, c(1, 0, 0)))
279 AIC(fit1, arima(presidents, c(2,0,0)),
[all …]
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| /dports/math/R-cran-dlmodeler/dlmodeler/man/ |
| H A D | dlmodeler.build.arima.Rd | 1 \name{dlmodeler.build.arima}
2 \alias{dlmodeler.build.arima}
3 \alias{dlmodeler.arima}
11 dlmodeler.arima(ar=c(), ma=c(), d=0,
13 name = "arima")
15 dlmodeler.build.arima(ar=c(), ma=c(), d=0,
17 name = "arima")
66 \keyword{ arima }
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| /dports/math/R-cran-forecast/forecast/man/ |
| H A D | arimaorder.Rd | 2 % Please edit documentation in R/arima.R
12 \code{\link[stats]{arima}}, \code{\link{Arima}}, \code{\link{auto.arima}},
26 WWWusage \%>\% auto.arima \%>\% arimaorder
30 \code{\link[stats]{ar}}, \code{\link{auto.arima}},
31 \code{\link{Arima}}, \code{\link[stats]{arima}}, \code{\link{arfima}}.
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| H A D | arima.errors.Rd | 2 % Please edit documentation in R/arima.R
3 \name{arima.errors}
4 \alias{arima.errors}
7 arima.errors(object)
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| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/arima/datasets/brockwell_davis_2002/ |
| H A D | __init__.py | 3 from statsmodels.tsa.arima.datasets.brockwell_davis_2002.data.dowj import dowj
4 from statsmodels.tsa.arima.datasets.brockwell_davis_2002.data.lake import lake
5 from statsmodels.tsa.arima.datasets.brockwell_davis_2002.data.oshorts import (
7 from statsmodels.tsa.arima.datasets.brockwell_davis_2002.data.sbl import sbl
|
| /dports/science/dynare/dynare-4.6.4/matlab/modules/dseries/src/utilities/x13/ |
| H A D | checkcommandcompatibility.m | 21 case 'arima'
23 error('x13:arima: ARIMA command is not compatible with AUTOMDL command!')
25 error('x13:arima: ARIMA command is not compatible with PICKMDL command!')
28 if ismember('arima', o.commands)
34 if ismember('arima', o.commands)
47 %$ o.arima('save','(d11)');
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| /dports/math/R-cran-forecast/forecast/ |
| H A D | NEWS.md | 52 * Improved auto.arima() stepwise search algorithm
133 * Added truncate argument to auto.arima()
138 * Arima() and auto.arima() now allow any argument to be passed to stats::arima().
180 * Made auto.arima more robust
189 * Added allowmean argument in auto.arima().
380 * Added seasonal argument to auto.arima().
664 * Yet more bug-fixes for auto.arima().
682 …* arima() function changed to Arima() to avoid the clash with the arima() function in the stats pa…
703 …he old grid-search method used by best.arima() is still available by using stepwise=FALSE when cal…
709 * Added include.drift to arima()
[all …]
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| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/arima/estimators/ |
| H A D | gls.py | 15 from statsmodels.tsa.arima.estimators.yule_walker import yule_walker
16 from statsmodels.tsa.arima.estimators.burg import burg
17 from statsmodels.tsa.arima.estimators.hannan_rissanen import hannan_rissanen
18 from statsmodels.tsa.arima.estimators.innovations import (
20 from statsmodels.tsa.arima.estimators.statespace import statespace
22 from statsmodels.tsa.arima.specification import SARIMAXSpecification
23 from statsmodels.tsa.arima.params import SARIMAXParams
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| /dports/devel/R-cran-broom/broom/man/ |
| H A D | tidy.Arima.Rd | 2 % Please edit documentation in R/stats-arima-tidiers.R
11 \item{x}{An object of class \code{Arima} created by \code{\link[stats:arima]{stats::arima()}}.}
40 fit <- arima(lh, order = c(1, 0, 0))
46 \code{\link[stats:arima]{stats::arima()}}
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| H A D | glance.Arima.Rd | 2 % Please edit documentation in R/stats-arima-tidiers.R
10 \item{x}{An object of class \code{Arima} created by \code{\link[stats:arima]{stats::arima()}}.}
44 fit <- arima(lh, order = c(1, 0, 0))
50 \code{\link[stats:arima]{stats::arima()}}
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| /dports/math/R-cran-Zelig/Zelig/man/ |
| H A D | zeligArimaWrapper.Rd | 2 % Please edit documentation in R/model-arima.R
5 \title{Estimation wrapper function for arima models, to easily fit with Zelig architecture}
10 Estimation wrapper function for arima models, to easily fit with Zelig architecture
|