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Apr 18, 2024Open Access
In this paper, we consider the estimation problem of the unknown link function in the nonparametric multiplicative regression model. Combining the penalized splines technique, a least product relative error estimation method is proposed, where a effective model degree of freedom is defined, then the smoothing parameter is chosen by some information criterions. Simulation studies show that these strategies work well. Some asymptotic properties are established. A real data set is analyzed to illus...
Jun 27, 2023Open Access
This paper presents the analysis of a two-stage negative binomial group testing estimator of the prevalence of a rare trait when imperfect diagnostic tests with known sensitivity and specificity were used. The study utilized the method of Maximum Likelihood Estimation (MLE) to obtain the estimator and the Cramer-Rao lower bound method to compute the Fischer information of the estimator. The properties of the constructed estimator are discussed and the efficiency of the constructed estimator rela...
May 27, 2022Open Access
Hirschfled (1935) posed the question. Is it always possible to introduce new variates for the rows and the columns of the contingency-table such that both regressions are linear. In reply, he derived the formulas of dual sealing. This approach was later employed by Lingoes (1963, 1968) who was obviously unaware of Hirschfeld’s study, but noted that the approach would use the basic theory and equation worked out by Guttman (1941). We have to use a graphic with linear regression to find optimal we...
May 27, 2022Open Access
In the presence of multicollinearity, ridge regression techniques result in estimated coefficients that are biased but have smaller variance than Ordinary Least Squares estimators and may, therefore, have a smaller Mean Squares Error (MSE). The ridge solution is to supplement the data by stochastically shrinking the estimates toward zero. In this study, we propose a new estimator to reduce the effect of multicollinearity and improve the estimation. We show by a simulation study that the MSE of t...
Apr 24, 2022Open Access
The term grey forecasting model has been comprehensively utilized in numerous research arenas and discovered valid outcomes. Nevertheless, the model possesses certain possible problems that necessitate improvement. It has been proven that, part of the foremost issues distressing the prediction accurateness of the model are initial and background values. Henceforth, a new modified GM(1,1) model through the combination of optimized initial value and background value has been recommended in this st...
Jan 29, 2022Open Access
GDP is frequently used as a way of national evaluations, as well as a way of measuring economic progress. This paper analyses a combination of time series models that are both linear and non-linear in making forecast of Ghana’s GDP. Ghana’s GDP current prices data from 1980 to 2019 were used in the analysis. Based on the AIC values, the best model was determined to be ARIMA (2, 2, 2) in modeling our data, except that it is heteroscedastic. The combination with non-linear GARCH (1, 1) model is us...
Nov 24, 2021Open Access
The method by Fry for detecting geometric anisotropy in stationary spatial point pattern is investigated. We quantify anisotropy by stretching and compressing the point process about the axis. Using a simulated Strauss point pattern, we first fit ellipsoids to the compressed pattern of pairwise difference vectors to estimate the direction of anisotropy. The strength of compression and the regularity of the point process are varied at different times and the corresponding effect on the estimated ...
Sep 30, 2021Open Access
Surface integrals of vector fields play an important role in the solutions of natural science and physical science. The Gauss theorem reduces the difficulty of directly computing surface integrals of vector fields. This paper introduces an approach for the computation of integral surfaces in vector fields and obtains a generalized mathematical expression based on Gauss theorem. Moreover, the computation time is investigated by two classical examples.
Oct 19, 2020Open Access
The accelerated failure time partial linear model allows the functional form of the effect of covariates to be possibly nonlinear and unknown. We propose to approximate the nonparametric component by cubic B-splines and construct a Gehan estimating function similar to that under the AFT model. Due to its non-smoothness, which will lead to computational challenge in estimating standard error, we propose a polynomial-based smoothing Gehan estimating function and compute the estimate of the paramet...
Jun 24, 2020Open Access
Human cancer, which has complex pathogenesis, is generally relative to the dysfunction of biological systems. Thus, our research is not at molecular level, but at system level, i.e. molecular network. In this paper, specially, we use PPI network. In order to construct a PPI network, we used the SSN method which is proposed by Professor X. Liu and others. The SSN method is distinct from the traditional network methods, especially in screening differential expressed genes. Besides, the traditional...
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