By K. Nachazel
Methodological strategies of the speculation of estimation of statistical parameters of time sequence and their program to hydrology and water engineering, quite the sector of reservoir-controlled runoffs, are handled during this quantity. For estimates use is made from random sequences generated for varied likelihood houses. This methodological process allows exam of the houses of random and systematic blunders of the parameters expected even for the asymmetrical likelihood distributions, that are common in hydrology and water engineering. This publication could be of curiosity to stochastic hydrologists.
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Additional info for Estimation Theory in Hydrology and Water Systems
Figure 10 shows the curve of spectral density of the filtered series of average annual flows of the Elbe in the DEin (Czechoslovakia) profile, where two extremes in the region of medium-long periods can be identified. The relatively most pronounced extreme corresponds to T = 15 years. Table 2 presents a survey of the more pronounced periodic components in the set of 29 selected time series. In all the cases, spectral densities were computed for the binomially filtered series. ); b) long periods (26 years and more).
As with point estimation, problems arise with the biassed estimators. Despite these drawbacks, we can however claim that interval estimates, provided of course they can be constructed at all, are a valuable methodological instrument wherever an assessment of the accuracy of the estimate is to be undertaken using the length of the interval.
If the relationships of correlation between the variables grow boundlessly weaker with increasing time remoteness z. With the longer real or synthetic series it can easily be demonstrated that the autocorrelation functions of the individual samples, though they may be derived from one and the same series (i. e. the same population), can differ quite considerably. That is why the study of the behaviour of the autocorrelation functions is of immense importance, for it provides the basis for the decision on the most suitable type of model for a given series.