EXPLORING APPROPRIATE REGRESSION MODEL TO FORECAST PRODUCTION OF RABI PULSE IN ODISHA, INDIA

Pre harvest forecast of agricultural production is essentially required for food security point of view. In this paper attempt has been made to develop model for forecasting the yield of kharif (Groundnut, paddy, maize) and rabi (wheat and mustard) crop of different district of middle Gujarat and no[r]

associated with the observations. Usually, SAS date, time, or datetime values are used for thisvariable. PROC ARIMA uses the ID= variable in the following ways:to validate the data periodicity. When the INTERVAL= option is specified, PROC ARIMAuses the ID variable to check the d[r]

Regression with Autocorrelated and Heteroscedastic ErrorsThe AUTOREG procedure provides regression analysis and forecasting of linear models withautocorrelated or heteroscedastic errors. The AUTOREG procedure includes the following features: estimation and prediction of[r]

is the 95% confidence interval for β1 . Since the interval does not include 0, we can not accept that β1 = 0. From the graphs, normality ofresiduals are acceptable (see the linear trend in quantile-quantile plot).(b) Write down the estimated regression line and use it to find a[r]

t+h,t, ω,where C(.) is some function that is nonlinear in the parameters, ω, in the vector offorecasts,ˆyt+h,t, or in both. There is a close relationship between time-varying andnonlinear combinations. For example, nonlinearities in the true data generating processcan le[r]

This paper attempts to analyse the status of agricultural credit disbursement in the state of Odisha. The analysis has revealed that the credit disbursed for the crop loan, term loan and allied loan has been increased over the period of time.The growth rates in crop loan disbursement among the insti[r]

instead of using artificial fertilization. Zebrafish hasbeen suggested to spawn in groups (Spence et al.2008) but a recent behavioural study showed that wildzebrafish spawn in pairs rather than in groups (Hutteret al. 2010). Therefore, we believe that our experimen[r]

casts from a correctly specified nonlinear model may be inferior to ones from a certainlinear model.There exist relatively large studies in which the forecasting performance of nonlinearmodels is compared with that of linear models using actual macroeconomic[r]

the vegetation recovered naturally after the original Pinus massoniana was cut; (2) Evergreen broad-leaved forest catchment: Schima Superba and C. ssa were planted after the Pinus massoniana was cut; (3) Mixed forest catchment: Q. chenil and Les-pedeza bicolor were planted in the original Pi[r]

The present study is entirely based upon secondary data. The secondary data related to area, production and productivity of total horticultural crops in India, Haryana and Odisha were taken from National horticulture board data base and respective state horticultural departments from 2005-06 to 2017[r]

a trend, theTrendoption is set to YES, and the subsequent diagnostic tests are performed onthe differenced series.3. Seasonality test.The resultant series is tested for seasonality. A seasonal dummy model withAR(1) errors is fit and the joint significance of the seasonal dummy est[r]

numerical standard error 29Subject Index I-25objective function 88observed transition model 883one step ahead prediction error 107one-step-ahead forecasts 54optic scanner data 985optimal action function 89optimal combination 141, 521optimal forecast 788, 854optimal hedging strategy 67o[r]

els with one predictor, so there are only a total of n models under consideration. Despiteruling out models with multiple predictors, he found that BMA can improve upon theequal-weighted combination forecasts.6. Empirical Bayes methodsThe discussion of BMA in the previous sectio[r]

Chickpea (Cicer arietinum L.) is one of the major rabi pulse crop and is a cheap source of protein. It has also advantages in the management of soil fertility particularly in dry lands and the semiarid tropics. Despite of low productivity of chickpea is attributed to Fusarium wilt disease which caus[r]

Pigeonpea (Cajanus cajan L.) is an important multipurpose pulse legume in the tropics and subtropics. The global production of pigeon pea is 4.32 million tonnes from an area of 5.32 m ha with a productivity of 813.2 kg/ha. India is the largest producer and consumer of pigeonpea with an area of 3.86[r]

Agricultural production depends upon many factors, of which weather is the major factor. Weather varies with space and time; hence, its forecast can help to minimize the farm losses through proper management of agricultural operations. The complete avoidance of all farm losses due to weather factor[r]

(node) the CART algorithm selects the explanatory vari-able and splitting value that gives the best discriminationbetween two outcome classes. A full CART algorithmadds nodes until they are homogenous or contains fewobservations (≥5 is the standard cut off in S-Plus). Theproblem of cre[r]

An investigation was carried out at Agrometeorological field, Central Research Farm, Odisha University of Agriculture and Technology, Bhubaneswar in rabi season, 2017 in natural condition on study of various aspects of effect of weather (maximum temperature, minimum temperature, rainfall, maximum re[r]

Models developed at Rothamsted in collaboration withothers are producing predictions based on possible climatescenarios (see Box 1).•Worldwide, the net effect of climate change will be todecrease stocks of organic carbon (C) in soils, thus releasingadditional carbon dioxi[r]

Agriculture plays a vital role in Indian economy. Among the cereals, Rice has shaped the culture, diet and economy of thousands of millions of people. The total Rice production in the world is 496.22 million metric tonnes as estimated by the United states Department of Agriculture in 2019 (USDA). In[r]