scholarly journals METODA ZANURZANIA REGRESJI W PRZYPADKU WYSTĘPOWANIA OBSERWACJI NIETYPOWYCH

2019 ◽  
Vol 20 (2) ◽  
pp. 83-92
Author(s):  
Małgorzata Kobylińska
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Least Squares Method ◽  
Regression Function ◽  
Maximum Depth ◽  
Two Dimensional ◽  
Structural Elements ◽  
Linear Regression Function ◽  
Regression Functions

This paper presents the application of the regression maximum depth for the estimation of linear regression function structural elements. For two-dimensional sets including untypical observations, regression functions were developed using the classical least squares method and a method based on the concept of observation depth measure in a sample. The effect of untypical observations on the estimated models has been noted.

Fuzzy C-Regression Models

2013 ◽  
Vol 278-280 ◽  
pp. 1323-1326
Author(s):  
Yan Hua Yu ◽  
Li Xia Song ◽  
Kun Lun Zhang
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Linear Models ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
Estimation Methods ◽  
Statistical Regression ◽  
Fuzzy Linear Regression ◽  
Fuzzy Degree

Fuzzy linear regression has been extensively studied since its inception symbolized by the work of Tanaka et al. in 1982. As one of the main estimation methods, fuzzy least squares approach is appealing because it corresponds, to some extent, to the well known statistical regression analysis. In this article, a restricted least squares method is proposed to fit fuzzy linear models with crisp inputs and symmetric fuzzy output. The paper puts forward a kind of fuzzy linear regression model based on structured element, This model has precise input data and fuzzy output data, Gives the regression coefficient and the fuzzy degree function determination method by using the least square method, studies the imitation degree question between the observed value and the forecast value.

A modified tangent-gas approximation for two-dimensional steady flow

1958 ◽  
Vol 4 (6) ◽  
pp. 600-606 ◽  
Author(s):  
G. Power ◽  
P. Smith
Keyword(s):  
Least Squares ◽  
Steady Flow ◽  
Variational Approach ◽  
Least Squares Method ◽  
Two Dimensional ◽  
Subsonic Flows ◽  
Von Karman ◽  
Straight Line ◽  
Volume Relationship ◽  
Pressure Volume Relationship

A set of two-dimensional subsonic flows past certain cylinders is obtained using hodograph methods, in which the true pressure-volume relationship is replaced by various straight-line approximations. It is found that the approximation obtained by a least-squares method possibly gives best results. Comparison is made with values obtained by using the von Kármán-Tsien approximation and also with results obtained by the variational approach of Lush & Cherry (1956).

scholarly journals Mortalité du sapin baumier défolié par la tordeuse des bourgeons de l'épinette dans la région de la Gatineau au Québec

1982 ◽  
Vol 58 (5) ◽  
pp. 213-219 ◽  
Author(s):  
Jean Beaulieu ◽  
Yvan J. Hardy
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
Random Number ◽  
Least Squares Method ◽  
Random Number Generator ◽  
Balsam Fir ◽  
Number Generator ◽  
Profit Analysis ◽  
Significant Difference

This paper presents a method of analysis which differentiates between spruce budworm caused mortality and regular mortality on balsam fir in the Gatineau region in Quebec. A first attempt was made using multiple linear regression and a uniform random number generator. In order to overcome the bias inherent to the least squares method when dealing with a binary (0,1) dependent variable, a profit analysis was also conducted. In this case, the parameters and their variance were estimated using likehood method. These two approaches proved to be equivalent when percent budworm caused mortality was compared within the 1958 to 1979 period covered by the data at hand, while the outbreak lasted from 1968 to 1975.In 1979, approximately 55% of the stems had been killed by the budworm, accounting for 53% of the volume. Maple-yellow birch associations were more affected than fir associations although no significant difference was found. Fir mortality was delayed by aerial spraying of insecticides but this advantage disappeared as soon as the spray operations came to an end.

Harmonizing biomass tables by generalized least squares

1985 ◽  
Vol 15 (2) ◽  
pp. 331-340 ◽  
Author(s):  
T. Cunia ◽  
R. D. Briggs
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Regression Function ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Sample Tree ◽  
Tree Data ◽  
Regression Techniques ◽  
Ordinary Least Squares Method

To construct biomass tables for various tree components that are consistent with each other, one may use linear regression techniques with dummy variables. When the biomass of these components is measured on the same sample trees, one should also use the generalized rather than ordinary least squares method. A procedure is shown which allows the estimation of the covariance matrix of the sample biomass values and circumvents the problem of storing and inverting large covariance matrices. Applied to 20 sets of sample tree data, the generalized least squares regressions generated estimates which, on the average were slightly higher (about 1%) than the sample data. The confidence and prediction bands about the regression function were wider, sometimes considerably wider than those estimated by the ordinary weighted least squares.

A crystallographic and spectroscopic study of mercury(II) dithiocarbamate

1981 ◽  
Vol 59 (18) ◽  
pp. 2746-2749 ◽  
Author(s):  
Chung Chieh ◽  
Sing Kwen Cheung
Keyword(s):  
Mass Spectrum ◽  
Spectroscopic Study ◽  
Least Squares ◽  
Least Squares Method ◽  
Two Dimensional ◽  
Polymeric Compound ◽  
Full Matrix ◽  
Space Group ◽  
Polymeric Networks ◽  
Ir Bands

Ammonium dithiocarbamate, H2NCS2NH4, decomposes easily but the anion forms a stable mercury(II) complex, the crystals of which are orthorhombic with a = 7.851(3), b = 17.565(7), c = 12.051(3) Å, and space group Pbca. The structure was solved by the Patterson method and refined by the full-matrix least-squares method to an R of 0.038 for 781 reflections. The structure consists of layers of two-dimensional polymeric networks. The dimeric subunits in the layer containing two each of mutually connected Hg atoms and dithiocarbamates are further linked by other bridging dithiocarbamates forming a sheet-like structure. Each Hg atom bonds to four S atoms from four separate dithiocarbamates with Hg—S distances of 2.499(4), 2.508(4), 2.533(4), and 2.629(4) Å. The ir bands observed were: ν(NH2), 3320, 3220, 3125; δ(NH2), 1600; ν(C—N), 1395; ρr(NH2), 1172; and v(C—S), 840 cm−1. The mass spectrum of this polymeric compound gave peaks corresponding to Hg, S2, CNH2, HNCS, S, CS2, S5, S4, S3, and S8 in the order of their intensities.

LEAST SQUARES MONTE CARLO CREDIT VALUE ADJUSTMENT WITH SMALL AND UNIDIRECTIONAL BIAS

2016 ◽  
Vol 19 (08) ◽  
pp. 1650048 ◽  
Author(s):  
MARK JOSHI ◽  
OH KANG KWON
Keyword(s):  
Monte Carlo ◽  
Least Squares ◽  
Global Financial Crisis ◽  
Regression Function ◽  
Cash Flows ◽  
Least Squares Monte Carlo ◽  
Early Exercise ◽  
Regression Functions ◽  
The Global Financial Crisis ◽  
Bermudan Swaptions

Credit value adjustment (CVA) and related charges have emerged as important risk factors following the Global Financial Crisis. These charges depend on uncertain future values of underlying products, and are usually computed by Monte Carlo simulation. For products that cannot be valued analytically at each simulation step, the standard market practice is to use the regression functions from least squares Monte Carlo method to approximate their values. However, these functions do not necessarily provide accurate approximations to product values over all simulated paths and can result in biases that are difficult to control. Motivated by a novel characterization of the CVA as the value of an option with an early exercise opportunity at a stochastic time, we provide an approximation for CVA and other credit charges that rely only on the sign of the regression functions. The values are determined, instead, by pathwise deflated cash flows. A comparison of CVA for Bermudan swaptions and cancellable swaps shows that the proposed approximation results in much smaller errors than the standard approach of using the regression function values.

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