nlme: Linear and Nonlinear Mixed Effects Models
線形・非線形混合効果モデル
> library(nlme)
バージョン: 3.1.121
関数名 | 概略 |
---|---|
ACF |
Autocorrelation Function |
ACF.gls |
Autocorrelation Function for gls Residuals |
ACF.lme |
Autocorrelation Function for lme Residuals |
Alfalfa |
Split-Plot Experiment on Varieties of Alfalfa |
allCoef |
Extract Coefficients from a Set of Objects |
anova.gls |
Compare Likelihoods of Fitted Objects |
anova.lme |
Compare Likelihoods of Fitted Objects |
as.matrix.corStruct |
Matrix of a corStruct Object |
as.matrix.pdMat |
Matrix of a pdMat Object |
as.matrix.reStruct |
Matrices of an reStruct Object |
asOneFormula |
Combine Formulas of a Set of Objects Assay Bioassay on Cell Culture Plate |
asTable |
Convert groupedData to a matrix |
augPred |
Augmented Predictions |
balancedGrouped |
Create a groupedData object from a matrix |
bdf |
Language scores |
BIC |
Bayesian Information Criterion |
BIC.logLik |
BIC of a logLik Object |
BodyWeight |
Rat weight over time for different diets |
Cefamandole |
Pharmacokinetics of Cefamandole |
coef<- |
Assign Values to Coefficients |
coef.corStruct |
Coefficients of a corStruct Object |
coef.gnls |
Extract gnls Coefficients |
coef.lme |
Extract lme Coefficients |
coef.lmList |
Extract lmList Coefficients |
coef.modelStruct |
Extract modelStruct Object Coefficients |
coef.pdMat |
pdMat Object Coefficients |
coef.reStruct |
reStruct Object Coefficients |
coef.varFunc |
varFunc Object Coefficients |
collapse |
Collapse According to Groups |
collapse.groupedData |
Collapse a groupedData Object |
compareFits |
Compare Fitted Objects |
comparePred |
Compare Predictions |
corAR1 |
AR(1) Correlation Structure |
corARMA |
ARMA(p,q) Correlation Structure |
corCAR1 |
Continuous AR(1) Correlation Structure |
corClasses |
Correlation Structure Classes |
corCompSymm |
Compound Symmetry Correlation Structure |
corExp |
Exponential Correlation Structure |
corFactor |
Factor of a Correlation Matrix |
corFactor.corStruct |
Factor of a corStruct Object Matrix |
corGaus |
Gaussian Correlation Structure |
corLin |
Linear Correlation Structure |
corMatrix |
Extract Correlation Matrix |
corMatrix.corStruct |
Matrix of a corStruct Object |
corMatrix.pdMat |
Extract Correlation Matrix from a pdMat Object |
corMatrix.reStruct |
Extract Correlation Matrix from Components of an reStruct Object |
corNatural |
General correlation in natural parameterization |
corRatio |
Rational Quadratic Correlation Structure |
corSpatial |
Spatial Correlation Structure |
corSpher |
Spherical Correlation Structure |
corSymm |
General Correlation Structure |
covariate<- |
Assign Covariate Values |
covariate<-.varFunc |
Assign varFunc Covariate |
Dialyzer |
High-Flux Hemodialyzer |
Dim |
Extract Dimensions from an Object |
Dim.corSpatial |
Dimensions of a corSpatial Object |
Dim.corStruct |
Dimensions of a corStruct Object |
Dim.pdMat |
Dimensions of a pdMat Object |
Earthquake |
Earthquake Intensity |
ergoStool |
Ergometrics experiment with stool types |
Fatigue |
Cracks caused by metal fatigue |
fdHess |
Finite difference Hessian |
fitted.glsStruct |
Calculate glsStruct Fitted Values |
fitted.gnlsStruct |
Calculate gnlsStruct Fitted Values |
fitted.lme |
Extract lme Fitted Values |
fitted.lmeStruct |
Calculate lmeStruct Fitted Values |
fitted.lmList |
Extract lmList Fitted Values |
fitted.nlmeStruct |
Calculate nlmeStruct Fitted Values |
fixed.effects |
Extract Fixed Effects |
fixef.lmList |
Extract lmList Fixed Effects |
formula.pdBlocked |
Extract pdBlocked Formula |
formula.pdMat |
Extract pdMat Formula |
formula.reStruct |
Extract reStruct Object Formula |
gapply |
Apply a Function by Groups |
Gasoline |
Refinery yield of gasoline |
getCovariate |
Extract Covariate from an Object |
getCovariate.corStruct |
Extract corStruct Object Covariate |
getCovariate.data.frame |
Extract Data Frame Covariate |
getCovariateFormula |
Extract Covariates Formula |
getCovariate.varFunc |
Extract varFunc Covariate |
getData |
Extract Data from an Object |
getData.gls |
Extract gls Object Data |
getData.lme |
Extract lme Object Data |
getData.lmList |
Extract lmList Object Data |
getGroups |
Extract Grouping Factors from an Object |
getGroups.corStruct |
Extract corStruct Groups |
getGroups.data.frame |
Extract Groups from a Data Frame |
getGroupsFormula |
Extract Grouping Formula |
getGroups.gls |
Extract gls Object Groups |
getGroups.lme |
Extract lme Object Groups |
getGroups.lmList |
Extract lmList Object Groups |
getGroups.varFunc |
Extract varFunc Groups |
getResponse |
Extract Response Variable from an Object |
getResponseFormula |
Extract Formula Specifying Response Variable |
getVarCov |
Extract variance-covariance matrix |
gls |
Fit Linear Model Using Generalized Least Squares |
glsControl |
Control Values for gls Fit |
glsObject |
Fitted gls Object |
glsStruct |
Generalized Least Squares Structure |
Glucose |
Glucose levels over time |
Glucose2 |
Glucose Levels Following Alcohol Ingestion |
gnls |
Fit Nonlinear Model Using Generalized Least Squares |
gnlsControl |
Control Values for gnls Fit |
gnlsObject |
Fitted gnls Object |
gnlsStruct |
Generalized Nonlinear Least Squares Structure |
groupedData |
Construct a groupedData Object |
gsummary |
Summarize by Groups |
Gun |
Methods for firing naval guns |
IGF |
Radioimmunoassay of IGF-I Protein |
Initialize |
Initialize Object |
Initialize.corStruct |
Initialize corStruct Object |
Initialize.glsStruct |
Initialize a glsStruct Object |
Initialize.lmeStruct |
Initialize an lmeStruct Object |
Initialize.reStruct |
Initialize reStruct Object |
Initialize.varFunc |
Initialize varFunc Object |
intervals |
Confidence Intervals on Coefficients |
intervals.gls |
Confidence Intervals on gls Parameters |
intervals.lme |
Confidence Intervals on lme Parameters |
intervals.lmList |
Confidence Intervals on lmList Coefficients |
isBalanced |
Check a Design for Balance |
isInitialized |
Check if Object is Initialized |
LDEsysMat |
Generate system matrix for LDEs |
lme |
Linear Mixed-Effects Models |
lmeControl |
Control Values for lme Fit |
lme.groupedData |
LME fit from groupedData Object |
lme.lmList |
LME fit from lmList Object |
lmeObject |
Fitted lme Object |
lmeScale |
Scale for lme Optimization |
lmeStruct |
Linear Mixed-Effects Structure |
lmList |
List of lm Objects with a Common Model |
lmList.groupedData |
lmList Fit from a groupedData Object |
logDet |
Extract the Logarithm of the Determinant |
logDet.corStruct |
Extract corStruct Log-Determinant |
logDet.pdMat |
Extract Log-Determinant from a pdMat Object |
logDet.reStruct |
Extract reStruct Log-Determinants |
logLik.corStruct |
Extract corStruct Log-Likelihood |
logLik.glsStruct |
Log-Likelihood of a glsStruct Object |
logLik.gnls |
Log-Likelihood of a gnls Object |
logLik.gnlsStruct |
Log-Likelihood of a gnlsStruct Object |
logLik.lme |
Log-Likelihood of an lme Object |
logLik.lmeStruct |
Log-Likelihood of an lmeStruct Object |
logLik.lmList |
Log-Likelihood of an lmList Object |
logLik.reStruct |
Calculate reStruct Log-Likelihood |
logLik.varFunc |
Extract varFunc logLik |
Machines |
Productivity Scores for Machines and Workers |
MathAchieve |
Mathematics achievement scores |
MathAchSchool |
School demographic data for MathAchieve |
matrix<- |
Assign Matrix Values |
matrix<-.pdMat |
Assign Matrix to a pdMat Object |
matrix<-.reStruct |
Assign reStruct Matrices |
Meat |
Tenderness of meat |
Milk |
Protein content of cows' milk |
model.matrix.reStruct |
reStruct Model Matrix |
Muscle |
Contraction of heart muscle sections |
Names |
Names Associated with an Object |
Names.formula |
Extract Names from a formula |
Names.pdBlocked |
Names of a pdBlocked Object |
Names.pdMat |
Names of a pdMat Object |
Names.reStruct |
Names of an reStruct Object |
needUpdate |
Check if Update is Needed |
needUpdate.modelStruct |
Check if a modelStruct Object Needs Updating |
Nitrendipene |
Assay of nitrendipene |
nlme |
Nonlinear Mixed-Effects Models |
nlmeControl |
Control Values for nlme Fit |
nlme.nlsList |
NLME fit from nlsList Object |
nlmeObject |
Fitted nlme Object |
nlmeStruct |
Nonlinear Mixed-Effects Structure |
nlsList |
List of nls Objects with a Common Model |
nlsList.selfStart |
nlsList Fit from a selfStart Function |
Oats |
Split-plot Experiment on Varieties of Oats |
Orthodont |
Growth curve data on an orthdontic measurement |
Ovary |
Counts of Ovarian Follicles |
Oxboys |
Heights of Boys in Oxford |
Oxide |
Variability in Semiconductor Manufacturing |
pairs.compareFits |
Pairs Plot of compareFits Object |
pairs.lme |
Pairs Plot of an lme Object |
pairs.lmList |
Pairs Plot of an lmList Object |
PBG |
Effect of Phenylbiguanide on Blood Pressure |
pdBlocked |
Positive-Definite Block Diagonal Matrix |
pdClasses |
Positive-Definite Matrix Classes |
pdCompSymm |
Positive-Definite Matrix with Compound Symmetry Structure |
pdConstruct |
Construct pdMat Objects |
pdConstruct.pdBlocked |
Construct pdBlocked Objects |
pdDiag |
Diagonal Positive-Definite Matrix |
pdFactor |
Square-Root Factor of a Positive-Definite Matrix |
pdFactor.reStruct |
Extract Square-Root Factor from Components of an reStruct Object |
pdIdent |
Multiple of the Identity Positive-Definite Matrix |
pdLogChol |
General Positive-Definite Matrix |
pdMat |
Positive-Definite Matrix |
[.pdMat |
Subscript a pdMat Object |
pdMatrix |
Extract Matrix or Square-Root Factor from a pdMat Object |
pdMatrix.reStruct |
Extract Matrix or Square-Root Factor from Components of an reStruct Object |
pdNatural |
General Positive-Definite Matrix in Natural Parametrization |
pdSymm |
General Positive-Definite Matrix Phenobarb Phenobarbitol Kinetics |
phenoModel |
Model function for the Phenobarb data |
Pixel |
X-ray pixel intensities over time |
plot.ACF |
Plot an ACF Object |
plot.augPred |
Plot an augPred Object |
plot.compareFits |
Plot a compareFits Object |
plot.gls |
Plot a gls Object |
plot.intervals.lmList |
Plot lmList Confidence Intervals |
plot.lme |
Plot an lme or nls object |
plot.lmList |
Plot an lmList Object |
plot.nffGroupedData |
Plot an nffGroupedData Object |
plot.nfnGroupedData |
Plot an nfnGroupedData Object |
plot.nmGroupedData |
Plot an nmGroupedData Object |
plot.ranef.lme |
Plot a ranef.lme Object |
plot.ranef.lmList |
Plot a ranef.lmList Object |
plot.Variogram |
Plot a Variogram Object |
pooledSD |
Extract Pooled Standard Deviation |
predict.gls |
Predictions from a gls Object |
predict.gnls |
Predictions from a gnls Object |
predict.lme |
Predictions from an lme Object |
predict.lmList |
Predictions from an lmList Object |
predict.nlme |
Predictions from an nlme Object |
print.summary.pdMat |
Print a summary.pdMat Object |
print.varFunc |
Print a varFunc Object |
qqnorm.gls |
Normal Plot of Residuals from a gls Object |
qqnorm.lme |
Normal Plot of Residuals or Random Effects from an lme Object |
Quinidine |
Quinidine Kinetics |
quinModel |
Model function for the Quinidine data |
Rail |
Evaluation of Stress in Railway Rails |
random.effects |
Extract Random Effects |
ranef.lme |
Extract lme Random Effects |
ranef.lmList |
Extract lmList Random Effects |
RatPupWeight |
The weight of rat pups |
recalc |
Recalculate Condensed Linear Model Object |
recalc.corStruct |
Recalculate for corStruct Object |
recalc.modelStruct |
Recalculate for a modelStruct Object |
recalc.reStruct |
Recalculate for an reStruct Object |
recalc.varFunc |
Recalculate for varFunc Object |
Relaxin |
Assay for Relaxin |
Remifentanil |
Pharmacokinetics of remifentanil |
residuals.gls |
Extract gls Residuals |
residuals.glsStruct |
Calculate glsStruct Residuals |
residuals.gnlsStruct |
Calculate gnlsStruct Residuals |
residuals.lme |
Extract lme Residuals |
residuals.lmeStruct |
Calculate lmeStruct Residuals |
residuals.lmList |
Extract lmList Residuals |
residuals.nlmeStruct |
Calculate nlmeStruct Residuals |
reStruct |
Random Effects Structure |
simulate.lme |
Simulate results from lme models |
solve.pdMat |
Calculate Inverse of a Positive-Definite Matrix |
solve.reStruct |
Apply Solve to an reStruct Object |
Soybean |
Growth of soybean plants |
splitFormula |
Split a Formula |
Spruce |
Growth of Spruce Trees |
summary.corStruct |
Summarize a corStruct Object |
summary.gls |
Summarize a gls Object |
summary.lme |
Summarize an lme Object |
summary.lmList |
Summarize an lmList Object |
summary.modelStruct |
Summarize a modelStruct Object |
summary.nlsList |
Summarize an nlsList Object |
summary.pdMat |
Summarize a pdMat Object |
summary.varFunc |
Summarize varFunc Object |
Tetracycline1 |
Pharmacokinetics of tetracycline |
Tetracycline2 |
Pharmacokinetics of tetracycline |
update.modelStruct |
Update a modelStruct Object |
update.varFunc |
Update varFunc Object |
varClasses |
Variance Function Classes |
varComb |
Combination of Variance Functions |
varConstPower |
Constant Plus Power Variance Function |
VarCorr |
Extract variance and correlation components |
varExp |
Exponential Variance Function |
varFixed |
Fixed Variance Function |
varFunc |
Variance Function Structure |
varIdent |
Constant Variance Function |
Variogram |
Calculate Semi-variogram |
Variogram.corExp |
Calculate Semi-variogram for a corExp Object |
Variogram.corGaus |
Calculate Semi-variogram for a corGaus Object |
Variogram.corLin |
Calculate Semi-variogram for a corLin Object |
Variogram.corRatio |
Calculate Semi-variogram for a corRatio Object |
Variogram.corSpatial |
Calculate Semi-variogram for a corSpatial Object |
Variogram.corSpher |
Calculate Semi-variogram for a corSpher Object |
Variogram.default |
Calculate Semi-variogram |
Variogram.gls |
Calculate Semi-variogram for Residuals from a gls Object |
Variogram.lme |
Calculate Semi-variogram for Residuals from an lme Object |
varPower |
Power Variance Function |
varWeights |
Extract Variance Function Weights |
varWeights.glsStruct |
Variance Weights for glsStruct Object |
varWeights.lmeStruct |
Variance Weights for lmeStruct Object |
Wafer |
Modeling of Analog MOS Circuits |
Wheat |
Yields by growing conditions |
Wheat2 |
Wheat Yield Trials |
gls
一般化最小二乗法による線形モデルへの当てはめ
Arguments
- object
- model
- model.
- data
- correlation
- weights
- subset
- method...
REML
制限付き最尤推定法,ML
最尤推定法 - na.action
- control
- verbose
- ...
- evaluate
> gls(model = follicles ~ sin(2 * pi * Time) + cos(2 * pi * Time),
+ data = Ovary,
+ correlation = corAR1(form = ~1 | Mare)) %>% {
+ summary(.) %>% print(.)
+ update(., weights = varPower()) %>% print(.)
+ }
Generalized least squares fit by REML
Model: follicles ~ sin(2 * pi * Time) + cos(2 * pi * Time)
Data: Ovary
AIC BIC logLik
1571.455 1590.056 -780.7273
Correlation Structure: AR(1)
Formula: ~1 | Mare
Parameter estimate(s):
Phi
0.7532079
Coefficients:
Value Std.Error t-value p-value
(Intercept) 12.216398 0.6646437 18.380373 0.0000
sin(2 * pi * Time) -2.774712 0.6450478 -4.301561 0.0000
cos(2 * pi * Time) -0.899605 0.6975383 -1.289685 0.1981
Correlation:
(Intr) s(*p*T
sin(2 * pi * Time) 0.000
cos(2 * pi * Time) -0.294 0.000
Standardized residuals:
Min Q1 Med Q3 Max
-2.41180365 -0.75405234 -0.02923628 0.63156880 3.16247697
Residual standard error: 4.616172
Degrees of freedom: 308 total; 305 residual
Generalized least squares fit by REML
Model: follicles ~ sin(2 * pi * Time) + cos(2 * pi * Time)
Data: Ovary
Log-restricted-likelihood: -779.4626
Coefficients:
(Intercept) sin(2 * pi * Time) cos(2 * pi * Time)
12.1882442 -2.8125374 -0.8291796
Correlation Structure: AR(1)
Formula: ~1 | Mare
Parameter estimate(s):
Phi
0.7633477
Variance function:
Structure: Power of variance covariate
Formula: ~fitted(.)
Parameter estimates:
power
-0.3838082
Degrees of freedom: 308 total; 305 residual
Residual standard error: 12.08639
gnls
一般化最小二乗法による非線形モデルへの当てはめ
Arguments
- model
- data
- params
- start
- correlation
- weights
- subset
- na.action
- naPattern
- control
- verbose
- ...
> gnls(model = weight ~ SSlogis(Time, Asym, xmid, scal),
+ data = Soybean,
+ weights = varPower())
Generalized nonlinear least squares fit
Model: weight ~ SSlogis(Time, Asym, xmid, scal)
Data: Soybean
Log-likelihood: -486.8974
Coefficients:
Asym xmid scal
17.356822 51.872316 7.620525
Variance function:
Structure: Power of variance covariate
Formula: ~fitted(.)
Parameter estimates:
power
0.8815436
Degrees of freedom: 412 total; 409 residual
Residual standard error: 0.3662752
Ovary
データセット。
> data("Ovary")
> str(Ovary)
Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 308 obs. of 3 variables:
$ Mare : Ord.factor w/ 11 levels "4"<"2"<"11"<"7"<..: 7 7 7 7 7 7 7 7 7 7 ...
$ Time : num -0.1364 -0.0909 -0.0455 0 0.0455 ...
$ follicles: num 20 15 19 16 13 10 12 14 13 20 ...
- attr(*, "formula")=Class 'formula' length 3 follicles ~ Time | Mare
.. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
- attr(*, "labels")=List of 2
..$ x: chr "Time in estrus cycle"
..$ y: chr "Number of ovarian follicles > 10 mm. diameter"
> head(Ovary)
Grouped Data: follicles ~ Time | Mare
Mare Time follicles
1 1 -0.13636360 20
2 1 -0.09090910 15
3 1 -0.04545455 19
4 1 0.00000000 16
5 1 0.04545455 13
6 1 0.09090910 10