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Utilize previous theta estimate in optimization #16

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Utilize previous theta estimate in optimization #16

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7e7dfde
Utilize previous `theta` estimate in optimization
telkamp7 Nov 29, 2023
8c7c046
Added bullet to NEWS.md
telkamp7 Nov 29, 2023
4a27148
Add another TODO
telkamp7 Nov 29, 2023
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4 changes: 4 additions & 0 deletions NEWS.md
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,10 @@

* Wrap the dispersion variable `phi` in `exp()` to ensure that it is a possible value.

## Improvements

* Now the starting guess for the models parameters, `theta`, is based on the previous round of optimization. This increases the performance and robustness of the paramter estimation.

# aeddo 0.1.1

## Patch
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8 changes: 7 additions & 1 deletion R/aeddo.R
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Expand Up @@ -127,6 +127,9 @@ aeddo <- function(
)
}

# Set starting guess for theta
theta <- init_theta # TODO: #17 Implement a method to infer the initial `theta`, `lower`, and `upper`

# Loop over the observations to perform windowed estimation
for (i in 1:(n_observation - k)) {
# Extract data point for this estimation window
Expand Down Expand Up @@ -160,7 +163,7 @@ aeddo <- function(

# Gather all arguments in a list for`do.call()`
optimiser_arguments <- list(
par = init_theta,
par = theta,
data = window_data,
formula = formula,
fn = nll_poisson_gamma,
Expand Down Expand Up @@ -216,6 +219,9 @@ aeddo <- function(
past_outbreaks <- past_outbreaks %>%
dplyr::bind_rows(reference_data)
}

# Set starting guess for theta given last round of optimization
theta <- optimized_param$par * 0.7
}

return(results)
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