Summarize the result of fitting an Ornstein-Uhlenbeck model to data. Output includes a parameter table with estimates, standard errors, and confidence intervals, as well as goodness-of-fit statistics.
Usage
# S3 method for class 'fit_affectOU'
summary(object, level = 0.95, ...)Arguments
- object
An object of class
fit_affectOU.- level
Confidence level for intervals (default 0.95).
- ...
Additional arguments (unused).
Value
An object of class summary_fit_affectOU containing:
- coefficients
Data frame with columns
estimate,se,lower, andupperfor each parameter.- log_likelihood
Maximized log-likelihood value.
- rmse
Root mean squared error.
- nobs
Number of observations.
- convergence
Optimizer convergence code (0 = success).
- level
Confidence level used.
- method
Estimation method used.
Examples
model <- affectOU(theta = 0.5, mu = 0, gamma = 1)
sim <- simulate(model, stop = 500, dt = 0.01, save_at = 0.1)
data <- as.data.frame(sim)
fitted <- fit(model, data = data$value, times = data$time)
summary(fitted)
#>
#> ── Fitted Ornstein-Uhlenbeck Model Summary ─────────────────────────────────────
#> Method: mle, 5001 observations
#>
#> ── Coefficients ──
#>
#> Estimate SE 95% CI
#> theta 0.481 0.045 [0.393, 0.570]
#> mu 0.106 0.094 [-0.078, 0.289]
#> gamma 1.007 0.010 [0.987, 1.027]
#>
#> ── Goodness of fit ──
#>
#> Log-likelihood: -1253.674
#> RMSE: 0.311