نتایج جستجو برای: variation linear regression method
تعداد نتایج: 2441469 فیلتر نتایج به سال:
kim and bishu (fuzzy sets and systems 100 (1998) 343-352) proposeda modification of fuzzy linear regression analysis. their modificationis based on a criterion of minimizing the difference of the fuzzy membershipvalues between the observed and estimated fuzzy numbers. we show that theirmethod often does not find acceptable fuzzy linear regression coefficients andto overcome this shortcoming, pr...
one of the most important number sequences in mathematics is fibonacci sequence. fibonacci sequence except for mathematics is applied to other branches of science such as physics and arts. in fact, between anesthetics and this sequence there exists a wonderful relation. fibonacci sequence has an importance characteristic which is the golden number. in this thesis, the golden number is observed ...
abstract: in the paper of black and scholes (1973) a closed form solution for the price of a european option is derived . as extension to the black and scholes model with constant volatility, option pricing model with time varying volatility have been suggested within the frame work of generalized autoregressive conditional heteroskedasticity (garch) . these processes can explain a number of em...
new statistic based models provide a wide area of prediction equipments for different science areas. among these fields biology have just entered the contest of interdisciplinary sciences. drug discovery is a long and expensive process which could be decreased with theoretical approaches. in this study, 500 reported assayed anti cancer molecules were extracted from science direct articles, sket...
In a multiple linear regression model, there are instances where one has to update the regression parameters. In such models as new data become available, by adding one row to the design matrix, the least-squares estimates for the parameters must be updated to reflect the impact of the new data. We will modify two existing methods of calculating regression coefficients in multiple linear regres...
Machine learning approaches are an attractive option for analyzing large-scale data to detect genetic variants that contribute to variation of a quantitative trait, without requiring specific distributional assumptions. We evaluate two machine learning methods, random forests and logic regression, and compare them to standard simple univariate linear regression, using the Genetic Analysis Works...
In this paper, an analytical method for noncircular shape extrusion is presented. Using this method, non-linear deformation field can be described with Hermit cubic spline which is prescribed by the boundary conditions of the die at its entryand exit. The upper bound method has been used to obtain optimum coefficient of the tangential boundary conditions. The results show that the optimum tange...
In this paper, an analytical method for noncircular shape extrusion is presented. Using this method, non-linear deformation field can be described with Hermit cubic spline which is prescribed by the boundary conditions of the die at its entryand exit. The upper bound method has been used to obtain optimum coefficient of the tangential boundary conditions. The results show that the optimum tange...
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