textslh_reg = { if (!view_ml_reg){ if (beta[1]>0){ return html`log-likelihood for observed data with the model Y | x ~ Pois(λ = exp(${beta[0]} + ${beta[1]}x)) is ${geomean_like_reg(regdata, beta).toPrecision(4)}`} else{ return html`log-likelihood for observed data with the model Y | x ~ Pois(λ = exp(${beta[0]} ${beta[1]}x)) is ${geomean_like_reg(regdata, beta).toPrecision(4)}`} } else{ if (ml_beta[1]>0){ return html`log-likelihood for observed data with the model Y | x ~ Pois(λ = exp(${beta[0]} + ${beta[1]}x)) is ${geomean_like_reg(regdata, beta).toPrecision(4)}
log-likelihood for observed data with the ML estimate Y | x ~ Pois(λ = exp(${ml_beta[0].toPrecision(4)} + ${ml_beta[1].toPrecision(4)}x)) is ${geomean_like_reg(regdata, ml_beta).toPrecision(4)}`} else{ return html`log-likelihood for observed data with the model Y | x ~ Pois(λ = exp(${beta[0]} ${beta[1]}x)) is ${geomean_like_reg(regdata, beta).toPrecision(4)}
log-likelihood for observed data with the ML estimate Y | x ~ Pois(λ = exp(${ml_beta[0].toPrecision(4)} ${ml_beta[1].toPrecision(4)}x)) is ${geomean_like_reg(regdata, ml_beta).toPrecision(4)}`} } }