From dfd2f5a9fa5465b79a70a13b6921b309f157d92e Mon Sep 17 00:00:00 2001 From: ronnyhdez Date: Fri, 18 Aug 2023 17:39:20 -0600 Subject: [PATCH] Ref #68 abbreviations just once --- chapter_2_lm.qmd | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/chapter_2_lm.qmd b/chapter_2_lm.qmd index fdaa247..d5d0a18 100644 --- a/chapter_2_lm.qmd +++ b/chapter_2_lm.qmd @@ -623,12 +623,11 @@ plot_grid(daily_grid, The @tbl-lm_monthly_results provides a summary of linear models used for GPP estimation at each site, employing the vegetation indices as predictors. For each site and predictor, the table includes the relevant model summary -statistics, such as r-squared, adjusted r-squared, and root mean square error -(RMSE). More metrics such as the p-value, the Akaike Information Criterion (AIC) -and Bayesian Information Criterion (BIC) are dispalyed in the -@tbl-complete_lm_monthly_results +statistics, such as R2, adjusted r-squared, and RMSE. More metrics such as the +p-value, the Akaike Information Criterion (AIC) and Bayesian Information +Criterion (BIC) are dispalyed in the @tbl-complete_lm_monthly_results -Based on the Root Mean Square Error (RMSE), NDVI performed less favourably on +Based on the RMSE, NDVI performed less favourably on two out of the three sites compared with the other indices. However, the performance difference among the sites was not substantial, with the Bartlett experimental forest exhibiting slightly better results on all of their GPP ~ VIs