trend_LM | R Documentation |
Trend R6 class
Trend R6 class
R6Class
object.
Object of R6Class
with methods for fitting GP model.
GauPro::GauPro_trend
-> GauPro_trend_LM
m
Trend parameters
m_lower
m lower bound
m_upper
m upper bound
m_est
Should m be estimated?
b
trend parameter
b_lower
trend lower bounds
b_upper
trend upper bounds
b_est
Should b be estimated?
new()
Initialize trend object
trend_LM$new( D, m = rep(0, D), m_lower = rep(-Inf, D), m_upper = rep(Inf, D), m_est = rep(TRUE, D), b = 0, b_lower = -Inf, b_upper = Inf, b_est = TRUE )
D
Number of input dimensions of data
m
trend initial parameters
m_lower
trend lower bounds
m_upper
trend upper bounds
m_est
Logical of whether each param should be estimated
b
trend parameter
b_lower
trend lower bounds
b_upper
trend upper bounds
b_est
Should b be estimated?
Z()
Get trend value for given matrix X
trend_LM$Z(X, m = self$m, b = self$b, params = NULL)
X
matrix of points
m
trend parameters
b
trend parameters (slopes)
params
trend parameters
dZ_dparams()
Derivative of trend with respect to trend parameters
trend_LM$dZ_dparams(X, m = self$m_est, b = self$b_est, params = NULL)
X
matrix of points
m
trend values
b
trend intercept
params
overrides m
dZ_dx()
Derivative of trend with respect to X
trend_LM$dZ_dx(X, m = self$m, params = NULL)
X
matrix of points
m
trend values
params
overrides m
param_optim_start()
Get parameter initial point for optimization
trend_LM$param_optim_start( jitter = FALSE, b_est = self$b_est, m_est = self$m_est )
jitter
Not used
b_est
If the mean should be estimated.
m_est
If the linear terms should be estimated.
param_optim_start0()
Get parameter initial point for optimization
trend_LM$param_optim_start0( jitter = FALSE, b_est = self$b_est, m_est = self$m_est )
jitter
Not used
b_est
If the mean should be estimated.
m_est
If the linear terms should be estimated.
param_optim_lower()
Get parameter lower bounds for optimization
trend_LM$param_optim_lower(b_est = self$b_est, m_est = self$m_est)
b_est
If the mean should be estimated.
m_est
If the linear terms should be estimated.
param_optim_upper()
Get parameter upper bounds for optimization
trend_LM$param_optim_upper(b_est = self$b_est, m_est = self$m_est)
b_est
If the mean should be estimated.
m_est
If the linear terms should be estimated.
set_params_from_optim()
Set parameters after optimization
trend_LM$set_params_from_optim(optim_out)
optim_out
Output from optim
clone()
The objects of this class are cloneable with this method.
trend_LM$clone(deep = FALSE)
deep
Whether to make a deep clone.
t1 <- trend_LM$new(D=2)
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