README mdoel imapc estiamtes up;oaded for gam models

HPCurtis · Jun 26, 2024 · b081c22 · b081c22
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diff --git a/R/data_anal_gam_ext.r b/R/data_anal_gam_ext.r
@@ -68,6 +68,12 @@ totalmean <- sum(Totalslaughteredimpact) * 1000
 totalupper <- sum(Totalslaughteredimpactupper) * 1000
 totallower <- sum(Totalslaughteredimpactlower) * 1000
 
+#Tax levy calculation.
+cattle_levy = 5 
+lost_revenue_mean = totalmean * cattle_levy
+lost_revenue_upper = totalupper * cattle_levy
+lost_revenue_lower = totallower * cattle_levy
+
 # Model plots----
 fitgam %>% draw() + xlab()
 fitgam %>% appraise()

diff --git a/README.md b/README.md
@@ -104,8 +104,8 @@ lost_revenue_lower = totallower * cattle_levy
 |------------------------|------|---------|---|
 | Total Cattle Slaughtered Linear|-7,408,400|-2,663,278|-12,153,521|
 | Total Tax Revenue Cost $(AUS) Linear|37,041,999|13,316,392|60,767,606|
-| Total Cattle Slaughtered GAM|-7,408,400|-2,663,278|-12,153,521|
-| Total Tax Revenue Cost $(AUS) GAM|37,041,999|13,316,392|60,767,606|
+| Total Cattle Slaughtered GAM|-5,526,122|-2,707,164|-8,345,080|
+| Total Tax Revenue Cost $(AUS) GAM|27,630,611|13,535,822|41,725,400|
 
 Table 1. Causal estimates of impact on the total number on cattle slaughtered post Coivd-19 and the associated tax lost. With associated 95% prediction intervals for uncertainty estimation.