The cumulative quantile regression function with censored and truncated covariate

2012 ◽  
Vol 21 (3) ◽  
pp. 238-249 ◽  
Author(s):  
S. M. Tse
2014 ◽  
Vol 631-632 ◽  
pp. 245-249
Author(s):  
Huan Wang ◽  
Jian Yuan Huang ◽  
Yong Sheng Yuan

Nonparametric quantile regression method can be used as the first choice for some biostatistical data. Since the nonparametric quantile regression curves are estimated individually, the quantile curves can cross, leading to an invalid distribution estimation for the response. A simple nonparametric quantile regression method is proposed to avoid the crossing problem. The method uses nonparametric conditional density function estimate instead of the conditional distribution estimate to assure quantile regression function monotonous. Both a simulation study and an analysis of real salmon lustrousness data show the significant improvement of the method in solving the quantile crossing problem for some kind of biological data.


2020 ◽  
Vol 1 (2) ◽  
pp. 58
Author(s):  
Bunga Aprilia ◽  
Anna Islamiyati ◽  
Anisa Anisa

Nonparametric quantile regression is used to estimate the regression function when assumptions about the shape of the regression curve are unknown. It is only assumed to be subtle by involving quantile values. One estimator in nonparametric regression is spline. The segmented properties of the spline provide more flexibility than ordinary polynomials. Therefore, the nature of the spline makes it possible to adapt more effectively to the local characteristics of a function or data. This study proposes to get the results of the estimation platelet count model to the hematocrit value of DHF. The optimal model obtained from the estimation of quadratic spline quantile regression is at quantile 0.5 with one knot and the GCV value is 41.5. The results of the estimation show that there is a decrease in platelet counts as the percentage of hematocrit increase.


Author(s):  
Ainārs GRĪNVALDS

The stand selection for cutting in tactical planning should be done according to the same principles like in strategic planning – to maximize net present value. The simple way of how to transfer the net present value maximization principle from strategic planning to tactical planning was created in Sweden. The method is based on annual changes in the net present value by postponing final felling. Forest inventory data and forestry modelling system was used for calculation of changes in net present value for pine, spruce, birch, aspen and black alder stands. And changes in net present value were described by regression function with factors from stand parameters. The regression function allows calculating annual changes in net present value for each stand. And stands with higher decrease in net present value have higher cutting priority. Stands selected for the final felling in strategic plan were compared with the stands selected in tactical plan with two methods, first, by using annual changes in the net present value, second, by traditional planning principles. Stands selected by annual changes in the net present value were similar to stands that were selected for cutting in strategic plan, but stands selected by traditional planning principles – not.


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