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The weighted kernel deconvolution approach is employed for measurement error adjustment and a new procedure for designing a variables plan allowing for uncertainty in the shape parameters of the underlying distribution is developed.
When a significant difference between groups was apparent, multiple comparisons were performed using the Bonferroni procedure with type-I error adjustment.
This paper proposes a measurement and adjustment procedure for virtual pivot errors using the R-test and investigates the influence of virtual pivot errors to the surface profile in bonnet polishing.
The adjustment procedure for virtual pivot errors is developed by means of mathematical analysis.
After the seeding procedure has been initiated and the marker traces been identified, the alignment is finally optimized through a bundle adjustment procedure by minimizing a reprojection error.
To control for probability of type I errors due to multiple comparisons, we used an adjustment procedure developed by Benjamini and Hochberg.
Third, association studies usually request a multiple testing adjustment procedure to ensure overall appropriate type I error rates, such as Bonferroni correction [7], [8] and false discovery rates [9], [10], [11].
Specifically, we used a Sidak step-down adjustment procedure [ 71, 72] to ensure an experimentwise Type I error rate of p <.05, correcting for the number of statistical comparisons made.
14 The following equation illustrates the adjustment procedure: Log (risk of stroke 1 − risk of sroke ) = linear predictor Y CAL = α CAL + Y VAL.
- Error correcting codes, linear error correcting codes.
- Error correcting codes, linear error correcting codes, the Hadamard code.
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CEO of Professional Science Editing for Scientists @ prosciediting.com