UV {mixedsde} | R Documentation |
Computation Of The Sufficient Statistics
Description
Computation of U and V, the two sufficient statistics of the likelihood of the mixed SDE
dX_j(t)= (\alpha_j- \beta_j X_j(t))dt + \sigma a(X_j(t)) dW_j(t)
.
Usage
UV(X, model, random, fixed, times)
Arguments
X |
matrix of the M trajectories. |
model |
name of the SDE: 'OU' (Ornstein-Uhlenbeck) or 'CIR' (Cox-Ingersoll-Ross). |
random |
random effects in the drift: 1 if one additive random effect, 2 if one multiplicative random effect or c(1,2) if 2 random effects. |
fixed |
fixed effects in the drift: value of the fixed effect when there is only one random effect, 0 otherwise. |
times |
times vector of observation times. |
Details
Computation of U and V, the two sufficient statistics of the likelihood of the mixed SDE
dX_j(t)= (\alpha_j- \beta_j X_j(t))dt + \sigma a(X_j(t)) dW_j(t) = (\alpha_j, \beta_j)b(X_j(t))dt + \sigma a(X_j(t)) dW_j(t)
with b(x)=(1,-x)^t
:
U : U(Tend) = \int_0^{Tend} b(X(s))/a^2(X(s))dX(s)
V : V(Tend) = \int_0^{Tend} b(X(s))^2/a^2(X(s))ds
Value
U |
vector of the M statistics U(Tend) |
V |
list of the M matrices V(Tend) |
References
See Bidimensional random effect estimation in mixed stochastic differential model, C. Dion and V. Genon-Catalot, Stochastic Inference for Stochastic Processes 2015, Springer Netherlands 1–28