The present study pertains to estimation of body weight of Vigova Super M, broiler ducks using linear and some non linear (log, inverse, quadratic, cubic, power, S, compound, logistic, growth and exponential) regression equations. Breast angle was considered as a predictor for estimation of the body weight. The results indicate that quadratic regression equation provided the most accurate estim...

We provide rigorous guarantees for the regression approach to structured output prediction. We show that the quadratic regression loss is a convex surrogate of the prediction loss when the output kernel satisfies some condition with respect to the prediction loss. We provide two upper bounds of the prediction risk that depend on the empirical quadratic risk of the predictor. The minimizer of th...

Tea components (tea polyphenols, catechins, free amino acids, and caffeine) are the key factors affecting quality of green tea. This study aimed to relate biochemical substances in tea soil nutrient composition effectiveness fertilization. Seventy samples their corresponding plantation were randomly collected from Xinyang City, China. The caffeine examined, as well pH, nitrate (NO3--N), ammoniu...

A central issue in contemporary applied mathematics is the development of simpler dynamical models for a reduced subset of variables in complex high dimensional dynamical systems with many spatio-temporal scales. Recently, ad hoc quadratic multi-level regression models have been proposed to provide suitable reduced nonlinear models directly from data. The main results developed here are rigorou...

In this paper, we define two restricted estimators for the regression parameters in a multiple linear regression model with measurement errors when prior information for the parameters is available. We then construct two sets of improved estimators which include the preliminary test estimator, the Stein-type estimator and the positive rule Stein type estimator for both slope and intercept, and ...

In this paper, we propose a unified non-quadratic loss function for regression known as soft insensitive loss function (SILF). SILF is a flexible model and possesses most of the desirable characteristics of popular non-quadratic loss functions, such as Laplacian, Huber’s and Vapnik’s ε-insensitive loss function. We describe the properties of SILF and illustrate our assumption on the underlying ...

Adaptive Ridge is a special form of Ridge regression, balancing the quadratic penalization on each parameter of the model. It was shown to be equivalent to Lasso (least absolute shrinkage and selection operator), in the sense that both procedures produce the same estimate. Lasso can thus be viewed as a particular quadratic penalizer. From this observation, we derive a fixed point algorithm to c...

Ito processes are the most common form of continuous semimartingales, and include diffusion processes. The paper is concerned with the nonparametric regression relationship between two such Ito processes. We are interested in the quadratic variation (integrated volatility) of the residual in this regression, over a unit of time (such as a day). A main conceptual finding is that this quadratic v...

Background: While COVID-19 epidemic has been spreading worldwide, its characteristics are still unclear. The development of good mathematical models for predicting prevalence and subsiding is strongly expected. curve shows how the increases subsides. This number persons found infected daily. To express this with a model, compartment model such as SIR used generally. However, parameter values th...