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Assuming that the true functional predictor and the slope function are smooth, we investigate a two-step estimating procedure where both the true functional predictor and the slope function are estimated through spline smoothing.
Let us assume that the slope function f is sufficiently smooth.
Assume that the present method (35) satisfies the Lipschitz condition (54) and the slope function f is sufficiently smooth.
So (y S_{H}, _{0} (y)= H y geq a), and hence (S_{H}, _{0} (y) geqfrac{a}{y}), which is a contradiction (note that the slope function is non-decreasing).
The rate of decline (slope function as %/year) averaged 0.710%/year of age, with a nonsignificantly steeper decline among women than men (0.756 vs. 0.631%/year), and 0.915%/year of lithium exposure, with a significantly greater (non-overlapping CIs) rate of decline among women than men (0.934 vs. 0.785%/year of lithium; Table 6).
In this algorithm, to derive a figure from a normal vector and the coordinate, we express the figure by a model function and then fit the differential calculus function (slope function) to data on the normal vector by using the least-squares method.
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Hs,s and Hs,r are the slope functions for suppression of growth of the sensitive and resistant populations.
These transfer functions modify simple step, pulse or change of slope functions to represent a range of possible effects that include a long-term change which occurs after a period of 'ramping up', and a sudden increase followed by (possibly oscillating) 'exponential decay'.
The right panel of Fig. 6 shows something unusual in this context – a downward sloping function across release years (adjusted R2 = 0.18, t(46) = − 3.41, p = 0.0014, d = 1.01), again without a hint of a quadratic function.
Simulations showed that cumulative infiltration normal to the slope as function of time is decreasing with increasing slope angles for similar vertical ponding depths, corresponding to equal amount of surface water on a given horizontal slope section.
(iv) Slope Sum Function.
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