Regression analysis has worldwide popularity in the field of analysis and the development of empirical methods. After regression model is found, one proceeds to use the model for prediction, or control, or the mechanism which has generated the data. Most people have the tendency to check the validity of the model.
The basic purpose of the regression model is to describe the rapport between a set of predictor variables and one or more responses.The regression models usage in practical life can act as a guide to us for many validation techniques.
When a model is prepared then mostly checkers go for validation model procedures which can be used and it is practical to do so. The following procedures are useful in checking the validity of the regression models
Check on model predictions and coefficients with physical theory – A check on model predictions and coefficients should be made as soon as the model is developed. If the negative predictions are released theoretically with wrong sign, thenit is estimated that the model is a result of poor estimation. Marquardt and Snee has provided three potential models for this data: a) A nine- term full quadratic model fitted by least squares; b) A five – term subset of the quadratic model fitted by least squares; c) A nine – term full quadratic model developed by ridge regression techniques.
Collection of new data to check model predictions – Another method of model validation is the collection of statics data which can be compared with the predictions of the model. If the data is collected in a proper form, then it provides an overall check on the entire model construction process.
Comparison of results with theoretical models and simulated data – In this method an empirical model is prepared to provide a simulated data developed from a theoretical model.
Data splitting – The data provided is divided into two parts namely estimation data and prediction data. If data is collected in a sequence at proper time, then data has an estimation set and the prediction set. For example, Cady and Allen used the press algorithm to develop a corn yield prediction equation from four years of data published by Laird and Cady.
PROCESS OF BUILDING A REGRESSION MODEL
Model building can be done in three to four steps –
On Time Delivery
Plagiarism Free Work
24 X 7 Live Help
Services For All Subjects
Best Price Guarantee
I was not able to concentrate on academics and co-curricular activities all at once and hence I decided to seek professional assistance. The expert writers took care of my essay report so well as if it was their own. So no complaints at all!
The service solution is extremely flexible that helps students to procure services anytime as they need one. I could connect to them at any time of the day which made me feel calm and relaxed.
My parents have been really happy with my academic performance lately, and all thanks to the team offering excellent support and academic help. Easy availability and a true choice of students around the world!
I got a bonus mark this semester due to offering an error-free thesis. My examiner was so impressed with my assignment that she offered me a bonus mark which further boosted my grade.