Tidal harmonic analysis and prediction with least-squares estimation and inaction method

2019 ◽  
Vol 220 ◽  
pp. 196-208 ◽  
Author(s):  
Sida Li ◽  
Lintao Liu ◽  
Song Cai ◽  
Guocheng Wang
2017 ◽  
Vol 36 (3) ◽  
pp. 944-952
Author(s):  
OT Badejo ◽  
SO Akintoye

In this work, 500 hourly water level tidal data were used to perform least squares tidal harmonic analysis. Eleven tidal constituents were used for the harmonic analysis. Astronomical arguments (v + u) and the nodal factor (f) were computed for each tidal constituent and at each observational period with a programme written in Matlab environment. The harmonic constants determined from the least squares tidal harmonic analysis were substituted into a tidal prediction model to predict hourly tidal data and tidal predictions at 5 minutes’ intervals. Series of high and low water heights from the tidal predictions made at 5 minutes’ intervals were determined and matched with their corresponding times. Autocorrelation at lags 1 to 30 for the residuals of the observed and predicted tidal data shows that there is no significant correlation in the range of the 30 lags. The series of residuals of the observed and predicted tidal data is therefore white noise.   http://dx.doi.org/10.4314/njt.v36i3.39


1972 ◽  
Vol 28 (03) ◽  
pp. 447-456 ◽  
Author(s):  
E. A Murphy ◽  
M. E Francis ◽  
J. F Mustard

SummaryThe characteristics of experimental error in measurement of platelet radioactivity have been explored by blind replicate determinations on specimens taken on several days on each of three Walker hounds.Analysis suggests that it is not unreasonable to suppose that error for each sample is normally distributed ; and while there is evidence that the variance is heterogeneous, no systematic relationship has been discovered between the mean and the standard deviation of the determinations on individual samples. Thus, since it would be impracticable for investigators to do replicate determinations as a routine, no improvement over simple unweighted least squares estimation on untransformed data suggests itself.


2020 ◽  
Vol 28 (10) ◽  
pp. 2651-2655 ◽  
Author(s):  
Yuhong Sheng ◽  
Kai Yao ◽  
Xiaowei Chen

Biometrics ◽  
1989 ◽  
Vol 45 (2) ◽  
pp. 657 ◽  
Author(s):  
Douglas H. Johnson

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