Obtains maximum likelihood estimates of the model parameters, filters, smooths and forecasts random components of the model for the following processes: 1) Brownian motion, 2) integrated Brownian motion, 3) integrated Ornstein-Uhlenbeck process, 4) stationary process with powered correlation function, 5) stationary process with Matern correlation function, under multivariate normal and t response distributions. It also contains miscellaneous functions for diagnostic checks, boostrap standard error calculation, etc.
● Data Source:
CranContrib
● Keywords:
● Alias: lmenssp-package
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Smooths random components of the mixed model with a stationary or non-stationary stochastic process component, under multivariate normal response distribution
● Data Source:
CranContrib
● Keywords: multivariate normal distribution, smoothing
● Alias: smoothed
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Filters random components of the mixed model with a stationary or non-stationary stochastic process component, under multivariate normal response distribution
● Data Source:
CranContrib
● Keywords: filtering
● Alias: filtered
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Obtains the maximum likelihood estimates of the parameters for linear mixed effects models with random intercept and a stationary or non-stationary stochastic process component, under multivariate normal response distribution
● Data Source:
CranContrib
● Keywords: maximum likelihood estimation, stochastic processes
● Alias: lmenssp
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Obtains the maximum likelihood estimates of the parameters by expectatio-maximisation (E-M) algorithm for linear mixed effects models with random intercept and a stationary or non-stationary stochastic process component, under multivariate normal t distribution
● Data Source:
CranContrib
● Keywords: E-M algorithm, maximum likelihood estimation
● Alias: lmenssp.heavy
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Calculates empirical quantiles of univariate data and theoretical quantiles of a t distribution with a given degrees-of-freedom
● Data Source:
CranContrib
● Keywords: quantile-quantile plot, univariate t distribution
● Alias: qqplot.t
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Calculates empirical variances for data sets with regularly or irregularly spaced time points, and plots the result
● Data Source:
CranContrib
● Keywords: variances
● Alias: var.inspect
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Calculates bootstrap standard errors for the parameter estimates obtained by lmenssp when Nelder-Mead algorithm is used
● Data Source:
CranContrib
● Keywords: bootstrap, standard error calculation
● Alias: boot.nm
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Calculates empirical variogram for data sets with regularly or irregularly spaced time points, and plots the result
● Data Source:
CranContrib
● Keywords: variogram
● Alias: variogram
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Smooths random components of the mixed model with a stationary or non-stationary stochastic process component, under multivariate t response distribution
● Data Source:
CranContrib
● Keywords: multivariate t distribution, smoothing
● Alias: smoothed.heavy
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