Least-squares collocation with integer parameters
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The prediction of spatially and/or temporal varying variates based on observations of these variates at some locations in space and/or instances in time, is an important topic in the various spatial and Earth sciences disciplines. This topic has been extensively studied, albeit under different names. In Geodesy it is generally referred to as least-squares collocation. The underlying model used is often of the trend-signal-noise type. This model is quite general and it encompasses many of the conceivable measurements. However, the methods of prediction based on these models have only been developed for the case the trend parameters are real-valued. In the present contribution we generalize the theory of least-squares collocation by permitting some or all of the trend parameters to be integer valued. We derive the solution of integer-based least-squares collocation and show how it compares to the solution of standard least-squares collocation.
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Teunissen, Peter (2003)Abstract. In this invited contribution a brief review will be presented of the integer estimation theory as developed by the author over the last decade and which started with the introduction of the LAMBDA method in 1993. ...
Teunissen, Peter. (2007)The prediction of spatially and/or temporal varying variates based on observations of these variates at some locations in space and/or instances in time, is an important topic in the various spatial and Earth sciences ...
Teunissen, Peter (2007)In this contribution, we extend the existing theory of minimum mean squared error prediction (best prediction). This extention is motivated by the desire to be able to deal with models in which the parameter vectors have ...