nlme migration¶
These examples assume an existing data frame d and fitted models. Import the
named functions from rparity. For statsmodels examples, import
statsmodels.api as sm and statsmodels.formula.api as smf.
See numerical accuracy and limitations and the option-level coverage when reproducing an R analysis.
| Use | R | Python |
|---|---|---|
| Independent GLS | gls(y~x,data=d) |
gls("y~x",d) |
| REML | gls(y~x,data=d,method="REML") |
gls("y~x",d,method="REML") |
| ML | gls(y~x,data=d,method="ML") |
gls("y~x",d,method="ML") |
| AR1 | gls(f,d,correlation=corAR1(form=~t\|g)) |
gls(f,d,correlation=corAR1(form="~t\|g")) |
| AR1 start | corAR1(value=.3,form=~t\|g) |
corAR1(value=.3,form="~t\|g") |
| Fixed AR1 | corAR1(value=.3,form=~t\|g,fixed=TRUE) |
corAR1(value=.3,form="~t\|g",fixed=True) |
| Compound symmetry | gls(f,d,correlation=corCompSymm(form=~1\|g)) |
gls(f,d,correlation=corCompSymm(form="~1\|g")) |
| Compound symmetry start | corCompSymm(value=.2,form=~1\|g) |
corCompSymm(value=.2,form="~1\|g") |
| Unstructured | gls(f,d,correlation=corSymm(form=~t\|g)) |
gls(f,d,correlation=corSymm(form="~t\|g")) |
| ARMA11 | corARMA(p=1,q=1,form=~t\|g) |
corARMA(p=1,q=1,form="~t\|g") |
| AR2 | corARMA(p=2,q=0,form=~t\|g) |
corARMA(p=2,q=0,form="~t\|g") |
| MA1 | corARMA(p=0,q=1,form=~t\|g) |
corARMA(p=0,q=1,form="~t\|g") |
| Group variance | gls(f,d,weights=varIdent(form=~1\|a)) |
gls(f,d,weights=varIdent(form="~1\|a")) |
| Variance ratios | varIdent(value=c(b=2),form=~1\|a) |
varIdent(value={"b":2},form="~1\|a") |
| Power variance | gls(f,d,weights=varPower(form=~v)) |
gls(f,d,weights=varPower(form="~v")) |
| Fitted power variance | varPower(form=~fitted(.)) |
varPower(form="~fitted(.)") |
| Exponential variance | gls(f,d,weights=varExp(form=~v)) |
gls(f,d,weights=varExp(form="~v")) |
| Fitted exponential variance | varExp(form=~fitted(.)) |
varExp(form="~fitted(.)") |
| Combined covariance | gls(f,d,correlation=corAR1(form=~t\|g),weights=varIdent(form=~1\|a)) |
gls(f,d,correlation=corAR1(form="~t\|g"),weights=varIdent(form="~1\|a")) |
| Coefficients | coef(m) |
m.coef() |
| Covariance | vcov(m) |
m.vcov() |
| Likelihood | logLik(m) |
m.logLik() |
| AIC | AIC(m) |
m.AIC() |
| BIC | BIC(m) |
m.BIC() |
| Summary | summary(m) |
m.summary() |
| Sequential ANOVA | anova(m,type="sequential") |
m.anova(type="sequential") |
| Marginal ANOVA | anova(m,type="marginal") |
m.anova(type="marginal") |
| Intervals | intervals(m) |
m.intervals() |
| Coefficients intervals | intervals(m,which="coef") |
m.intervals(which="coef") |
| Predict | predict(m,newdata=nd) |
m.predict(newdata=nd) |
| Residuals | resid(m,type="normalized") |
m.residuals(type="normalized") |
| Fitted | fitted(m) |
m.fitted() |