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Bootstrapping paramétrico, semiparamétrico y no paramétrico para modelos mixtos
Los siguientes injertos se toman de este artículo . Soy novato en bootstrap e intento implementar el bootstrapping paramétrico, semiparamétrico y no paramétrico para el modelo mixto lineal con R bootpaquete. Código R Aquí está mi Rcódigo: library(SASmixed) library(lme4) library(boot) fm1Cult <- lmer(drywt ~ Inoc + Cult + (1|Block) + …
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r
mixed-model
bootstrap
central-limit-theorem
stable-distribution
time-series
hypothesis-testing
markov-process
r
correlation
categorical-data
association-measure
meta-analysis
r
anova
confidence-interval
lm
r
bayesian
multilevel-analysis
logit
regression
logistic
least-squares
eda
regression
notation
distributions
random-variable
expected-value
distributions
markov-process
hidden-markov-model
r
variance
group-differences
microarray
r
descriptive-statistics
machine-learning
references
r
regression
r
categorical-data
random-forest
data-transformation
data-visualization
interactive-visualization
binomial
beta-distribution
time-series
forecasting
logistic
arima
beta-regression
r
time-series
seasonality
large-data
unevenly-spaced-time-series
correlation
statistical-significance
normalization
population
group-differences
demography