تقدير متوسطات الاستجابة لمرض سرطان الثدي للعلاج باستخدام الأنواع المختلفة لدوال النواة

الملخص EN

There are two main sets of statistical models, nonparametric regression models and parametric regression models, which can be used when the explanatory variables are continuous or discrete variables and nonparametric regression which is used only when the explanatory variables continuous and probability distribution un known.

The Nonparametric regression has a great importance in many of studieswhere the nature of the relationship between the explanatory variables and the dependent variable is un known ,or in the other words the probability distribution of these variables is un known and is a problem in response breast cancer treatment studies in which the nature of the relationship between the variables under study and response to treatment unknown , breast cancer is one of the most common types of cancers in yemen , and the nature of the response to treatment is not known, so study aimed to estimate the mean response.

The limits of the study: The study included patients with breast cancer in center Hope cancer in republic hospital in Aden since the establishment of the center in ٢٠٠٧ and until ٢٠٠١.

The methods used in the estimates nonparametric The different methods used in the estimating the nonparametric regression function, as kernel method ,nearest neighborhood method syematric neighborhood and spline regression method with concentration the kernel method by Ebanchicnove formula ,which is considered one of the most common kernel function , and most efficiency ,and the different formulas used to estimate the kernel function such as formula ,Nadaraya-Watson ,Gasser-Muler, Priestliy –chao with concentricity on Nadaraya-Watson formula can be used only if the model used in the study is to be a random design model, where all the explanatory variables , random variables change from one individual to another in other words explanatory variable is seen as a random variable change with the samples, as is the case in state of the explanatory variables used in our study , where we find that each of the age and size of the tumor and the amount of the property and body surface area change from one patient to another.