In this paper we obtain a consistent estimator when there exist some measurement errors and multicollinearity in the instrumental variables in a two stage least square estimation of parameters. We investigate the asymptotic distribution of the proposed estimator and discuss its properties using some theoretical proofs and a simulation study. A real numerical application is also provided for mor...

spatiality assessment of groundwater pollution is very important to determine water quality condition, pollution sources and management decisions. in this case, gis and geostatistics methods can be useful tools. spatiality of groundwater quality parameters, in relation with various land uses, can be very extremely. therefore water samples from 52 wells in the kurdan area were analyzed in this s...

Keeping the water table at a favorable level is quite significant for a sustainable management of groundwater plans. Various management measures need to know the spatial and temporal behavior of groundwater. Therefore, the measurement of groundwater levels are generally carried out at spatially random locations in the field; whereas, most of the groundwater models requires these measurement at ...

In this paper, we investigate Gaussian process regression models where inputs are subject to measurement error. In spatial statistics, input measurement errors occur when the geographical locations of observed data are not known exactly. Such sources of error are not special cases of “nugget” or microscale variation, and require alternative methods for both interpolation and parameter estimatio...

This work is devoted to the construction of new kriging-based interpolating position-dependent subdivision schemes for data reconstruction. Their originality stands in the coupling of the underlying multi-scale framework associated to subdivision schemes with kriging theory. Thanks to an efficient stencil selection, they allow to cope the problem of non-regular data prediction while keeping the...

This paper investigates the benefits of integrating coarse resolution satellite-derived precipitation estimates with quasi-point rain gauge data for generating a fine spatial resolution precipitation map product. To integrate the two precipitation data sources, a geostatistical downscaling and integration approach is presented that can account for the differences in spatial resolution between d...

drought monitoring is a fundamental component of drought risk management. it is normally performed usingvarious drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables.in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolationof spatially referenced data and the prediction of values fo...