EstParamNormal function

Maximization Of The Log Likelihood In Mixed Stochastic Differential Equations

Maximization of the loglikelihood of the mixed SDE with Normal distribution of the random effects $dXj(t)= (\alpha_j- \beta_j Xj(t))dt + \sigma a(Xj(t)) dWj(t)$, done with likelihoodNormal

EstParamNormal(U, V, K, random, estim.fix, fixed = 0)

Arguments

• U: matrix of M sufficient statistics U
• V: list of the M sufficient statistics matrix V
• K: number of times of observations
• 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.
• estim.fix: 1 if the fixed parameter is estimated, when random 1 or 2 , 0 otherwise
• fixed: value of the fixed parameter if known (not estimated)

Returns

• mu: estimated value of the mean

• Omega: estimated value of the variance

• BIChere: BIC indicator

• AIChere: AIC indicator