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