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Oct 17, 2024Open Access
Breast cancer remains a significant global health challenge, with prognosis and treatment decisions largely dependent on clinical characteristics. Accurate prediction of patient outcomes is crucial for personalized treatment strategies. This study employs survival analysis techniques, including Cox proportional hazards and parametric survival models, to enhance the prediction of the log odds of survival in breast cancer patients. Clinical variables such as tumor size, hormone receptor status, HE...
Sep 24, 2024Open Access
Homeownership is part of the “American Dream” and a key tool for households to build wealth. However, increasing house prices have made homeownership less attainable recently. In order to determine the factors affecting home supply, we used non-parametric approaches. Some of them include the Nadaraya-Watson estimator, Local Polynomial estimator, B-spline, P-spline, and the Adapted He approach. The latter is particularly useful when dealing with outliers or non-standard conditional distributions ...
Aug 15, 2024Open Access
Multiplicative regression model has been proven to be an excellent model for analyzing data with positive responses. When constructing the confidence regions of the regression parameters, one had to either directly estimate the asymptotic covariance matrix involving the estimation of the unknown density function of the model error, then the normal approximation can be conducted, or resort to the time-consuming resampling methods to avoid the difficulty of estimating the covariance matrix. Recent...
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 ...
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