Obviously, you can understand the related process from the title of this section, i.e. Introduction to Data Tool?Ģ- Convert daily data to monthly or seasonally So, Agrimetsoft has developed "Data Tool" for solving this issue. Several types of research and scholars have problems to calculate different indices, in this regards. There are different methods for doing this activity which is called in a different name, such as "Efficiency criteria", "Statistical measures of model performance", "Statistical methods for accuracy", "Model evaluation technique", "Evaluation Statistics", and etc.
This step is an essential and vital part of the different process of engaging in a project. It is necessary to know that validation process commonly includes a criteria definition that relies on mathematical measurements of how well model-produced estimates simulate the observed values.
In following this manuscript, you can learn that how can you reshape your data and how can you implement and use different statistical methods for the accuracy of your model and in your model evaluation through Data Tool. So, "Data Tool" is an Excel add-ins tool for reshaping and sorting data in excel and convert daily data to monthly or seasonally, and finally calculate efficiency criteria such as Root Mean Square Error, Nash Sutcliffe model Efficiency coefficient, Mean Absolute Error, and other ones. Before calculating these essential indices with Data Tool, we should reshape the data in a specific format which can able to run them. In this regards, Agrimetsoft has decided to progress a comprehensive Excel add-ins that users can easily sort and reshape their data, then apply the mentioned indices over the sorted data. So, we need an applicable tool for this aim. Also, the evaluation of model performance, i.e., to compare model-produced estimates with observed/reliable values, is a fundamental step for model development and use. Draw CDF/PDF graphĪssessing the accuracy of predictive models is critical because predictive models have been increasingly used across various disciplines and predictive accuracy determines the quality of resultant predictions. Reshape data and calculate RMSE, NSE, Pearson Correlation, MBE, etc.