Urmil Verma

Development of State Space Models with Weather as Exogenous Input for Sugarcane Yield Prediction in Haryana

Ekta Hooda & Urmil Verma · Advances in Research · 2020

Parameter constancy is a fundamental issue for empirical models to be useful for forecasting, analyzing or testing any theory. Unlike classical regression analysis, the state space models (SSM) are time varying parameters models as they allow for known changes in the structure of...

Open access Research Article 10.9734/air/2020/v21i530202

Principal Component Technique for Pre-harvest Crop Yield Estimation Based on Weather Input

Megha Goyal, Salinder ., Suman . & Urmil Verma · Advances in Research · 2018

Forecasting of crop production is one of the most important applications of statistics in agriculture. Such predictions before harvest are needed by the national and state governments for various policy decisions relating to storage, distribution, pricing, marketing, import- expo...

Open access Research Article 10.9734/AIR/2018/42670