996 resultados para Kriging chart


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Chart of unnumbered estimate of work done by John Williams. This is signed by Fred Holmes, May 1857.

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Chart of estimate #18 of work done by John Williams. This is signed by Fred Holmes, June 1857.

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Chart of estimate #18c of work done by John Williams, June, 1857.

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Chart of estimate #19 of work done by John Williams, July 1857.

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Chart of final estimate #20 of work done by John Williams, n.d.

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Chart of station 2, crop sections of the old back ditch on the south side of the feeder, station 45, station 118 and the total length from the culvert to lot no. 5. This is signed by Fred Holmes, April 13, 1857.

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Chart of final estimate of work done on section no.10, locks 24, 25 and 26 by Sharp and Quinn, contractors commenced Nov. 1843 and was finished May 1845.

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Chart of final estimate of work done between Port Dalhousie and lock no.2 by Robert Jobson, contractor. The work commenced Nov. 1846 and was finished April 1847 on sections A and B, July 1847.

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Chart of land drainage for the Welland Canal final estimate of work done on sections no.1, 2 and 3 on the road below lock no. 2 leading to Port Dalhousie. Work commenced Nov. 1846 and finished July 1847. Road work and the waste weir no.1 to Port Dalhousie work commenced Aug. 1847 and finished Sept. 1847, Nov.1, 1847.

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Chart containing the statement of amount required to complete the canal, March 15, 1848.

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Chart of approximate quantity of excavation in slides in the deep cut, July 1, 1848.

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Chart of calculations regarding quarrying, cutting, transportation and cement, n.d.

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Kriging is an interpolation technique whose optimality criteria are based on normality assumptions either for observed or for transformed data. This is the case of normal, lognormal and multigaussian kriging. When kriging is applied to transformed scores, optimality of obtained estimators becomes a cumbersome concept: back-transformed optimal interpolations in transformed scores are not optimal in the original sample space, and vice-versa. This lack of compatible criteria of optimality induces a variety of problems in both point and block estimates. For instance, lognormal kriging, widely used to interpolate positive variables, has no straightforward way to build consistent and optimal confidence intervals for estimates. These problems are ultimately linked to the assumed space structure of the data support: for instance, positive values, when modelled with lognormal distributions, are assumed to be embedded in the whole real space, with the usual real space structure and Lebesgue measure

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Pie chart animation

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Animation