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On Specification And Statistical Inference In Single Equation Regression Models., Nityananda Sarkar Dr.
On Specification And Statistical Inference In Single Equation Regression Models., Nityananda Sarkar Dr.
Doctoral Theses
This thesis attempta to cansider and provids solutions to viat nay be broadly decribed na Bone problems of speciification and satatistical inforence in single equation lineur regression models. It co sists of three parte, each having several chepters. The firat part in devoted to sme problems connec ted vith the use of the wall-imown Bor-Cox (BC) tranaformation of variablee in single equetion ragreanion nodels. In the other two parts we exanine an autocorrelated linear regreasion nodel from a rather unconventional angle. Precisely, we consider the problema which arise when the error tem in an autocorre lated linear regression nodel is …
Estimation In Errors-In-Variables Models., Manoranjan Pal Dr.
Estimation In Errors-In-Variables Models., Manoranjan Pal Dr.
Doctoral Theses
In many econometric investigations, the 'errors-in variables' (EIVs) are not negligible (Morgenstern, 1963). Examination of 25 series relating to national accounts by Langaskens and Rijekeghan (1974) showed that the standard deviations of the errors ranged from 5 to 77 per cent of the average value of the corresponding variable. Such errors may vitiate least-squares (LS) estimation of regression coefficients (Johnaton, 1972). The well-known methods (ML; IV, including grouping method) proposed for handling classical EIV model (EMM) in regression analysis muffer from serious linitations. Same of them make strong distributional assumptions about the errors (and the regressors) and/or assume prier knowledge …
Estimation Of A Common Mean And Recovery Of Inter Block Information., Chunni Gopal Bhattacharya Dr.
Estimation Of A Common Mean And Recovery Of Inter Block Information., Chunni Gopal Bhattacharya Dr.
Doctoral Theses
The problem of conbining several estimates of an unknown quentity to obtain an eetimete of Improved precieion arises in meny spheres of application of etatistics, To begin with let us consider the following simple inadelt1 =+4, 1- 1,...,kwhere u ie an unknown quantity and e, e ere errora with a common menn zero end a common veriance o. If we make no further asoumption about the distribution of e,s, the GAuas-Markoff theorem tells us that among sll unbtaved lineer combinationa ofr ya, the least squAre estimator i * Iy /k of u hes the minimum variance. If ,s are jointly …