Spatial–temporal variation of casuarina spread in Cauvery delta and north eastern zone of Tamil Nadu, India: a spatial autoregressive model

2016 ◽  
Vol 45 (1) ◽  
pp. 1-7 ◽  
Author(s):  
M. Vijayabhama ◽  
R. Jaisankar ◽  
S. Varadha Raj ◽  
K. Baranidharan
Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1448
Author(s):  
Xuan Liu ◽  
Jianbao Chen

Along with the rapid development of the geographic information system, high-dimensional spatial heterogeneous data has emerged bringing theoretical and computational challenges to statistical modeling and analysis. As a result, effective dimensionality reduction and spatial effect recognition has become very important. This paper focuses on variable selection in the spatial autoregressive model with autoregressive disturbances (SARAR) which contains a more comprehensive spatial effect. The variable selection procedure is presented by using the so-called penalized quasi-likelihood approach. Under suitable regular conditions, we obtain the rate of convergence and the asymptotic normality of the estimators. The theoretical results ensure that the proposed method can effectively identify spatial effects of dependent variables, find spatial heterogeneity in error terms, reduce the dimension, and estimate unknown parameters simultaneously. Based on step-by-step transformation, a feasible iterative algorithm is developed to realize spatial effect identification, variable selection, and parameter estimation. In the setting of finite samples, Monte Carlo studies and real data analysis demonstrate that the proposed penalized method performs well and is consistent with the theoretical results.


2019 ◽  
Vol 42 (3) ◽  
pp. 225-230
Author(s):  
K.R. Sasidharan ◽  
◽  
G. Ramesh ◽  

Casuarina equisetifolia is an exotic, fast growing, multipurpose tree species grown in Tamil Nadu. Altogether, about 40 species of insects have been recorded on C. equisetifolia in Tamil Nadu State. Among them, the bark eating caterpillar, Indarbela quadrinotata is considered as the most destructive pest in plantations. Wide variation in the infestation levels of bark eating caterpillar was noticed in Casuarina plantations grown under four agro-climatic zones of Tamil Nadu; the Cauvery Delta Zone showed highest intensity of attack, followed by the North Eastern Zone and the Southern Zone in the decreasing order of infestation, while the High Rainfall Zone was not affected by the pest. Plantations of younger age suffered from higher levels of infestation, compared to that of older ones. Among the climatological parameters, the minimum temperature had significant positive correlation with the pest infestation. Apart from the naturally occurring entomopathogenic fungus, Beauveria bassiana, the botanical formulations such as Melia azedarach seed kernel extract (5%), Pongamia pinnata seed oil (5%), Hydnocarpus pentandra seed oil (10,000 ppm) and Neem oil (5%) were found to be very effective in managing the pest under field condition.


2014 ◽  
Vol 2 (3) ◽  
pp. 226-235
Author(s):  
Yuanqing Zhang

Abstract In this paper, we study estimation of a partially specified spatial autoregressive model with heteroskedasticity error term. Under the assumption of exogenous regressors and exogenous spatial weighting matrix, we propose an instrumental variable estimation. Under some sufficient conditions, we show that the proposed estimator for the finite dimensional parameter is root-n consistent and asymptotically normally distributed and the proposed estimator for the unknown function is consistent and also asymptotically distributed though at a rate slower than root-n. Monte Carlo simulations verify our theory and the results suggest that the proposed method has some practical value.


1982 ◽  
Vol 14 (8) ◽  
pp. 1023-1030 ◽  
Author(s):  
L Anselin

This note considers a Bayesian estimator and an ad hoc procedure for the parameters of a first-order spatial autoregressive model. The approaches are derived, and their small sample properties compared by means of a Monte Carlo simulation experiment.


Sign in / Sign up

Export Citation Format

Share Document