نتایج جستجو برای: linear regression model over the period 1959
تعداد نتایج: 16504007 فیلتر نتایج به سال:
abstract the current study sets out 1) to investigate the strategic needs of iranian efl learners in reading literary and non-literary texts; 2) to shed some light on the differences between reading literary and non-literary texts; and 3) to specify the differences in the interaction of participants with texts while reading two literary subgenres ( i.e., short story and literary essays). to ...
abstract: in this study an appropriate computational approach was presented for estimating the boiling temperatures of 41 different types of olefins and their derivatives. based on the guidelines of this approach, several structural indices related to the organic components were applied using graph theory. meanwhile, in addition to evaluating the relation between the boiling temperatures of ole...
a number of 5558 lambing records of 2245 mehraban ewes, collected during years 1995 to 2010 were utilized to estimate the variance components and heritability for the number of lambs per lambing, making use of b-spline random regression models. the fixed factors affecting the studied trait were identified using general linear model analysis as well as sas software, where flock-year-season and ...
aim : to determine the associated factors of reflux duration, using quantile regression model. background : reflux is one of the most prevalent gastrointestinal disorders. statistical tools are widely used to assess the associated factors on reflux severity and frequency. patients and methods : a door to door questionnaire has been used to evaluate gastrointestinal symptoms including reflux an...
Background and purpose: Jajrood River is one of the major drinking water supply rivers in Tehran, so, the effects of climate change on its quantitative and qualitative resources are highly important. This study aimed at investigating the effect of climate change on organic carbon removal in Jajrood basin. Materials and methods: In this descriptive cross-sectional study, CanESM2 general circula...
In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...
The purpose of this paper is to examine and evaluate the effects of government intervention on the Iranian economy over the last few decades. It is shown that public expenditures affect the value added of each economic sector not only simultaneously, but lagged over several periods. Regression results show that the value added from the agricultural sector has never been affected by government e...
The mode of a distribution provides an important summary of data and is often estimated based on some non-parametric kernel density estimator. This article develops a new data analysis tool called modal linear regression in order to explore highdimensional data. Modal linear regression models the conditional mode of a response Y given a set of predictors x as a linear function of x. Modal linea...
چکیده روش های متعددی برای برآورد رواناب حاصل از بارش در حوضه های آبریز وجود دارد. یکی از این روش ها استفاده از مدل های هیدرولوژیکی است. با استفاده از مدل های هیدرولوژیکی و شبیه سازی فرآیندهای هیدرولوژیکی می توان با صرف کمترین زمان و هزینه، رواناب و مولفه های دیگر چرخ? هیدرولوژیکی را برآورد کرد. از آنجا که در حوضه های آبریز اندازه گیری تمام کمیت های مورد نیاز برای تحلیل رواناب ممکن نیست، انتخاب...
For the valuation of the renewable energy investments, providing private investors with a financial incentive to accelerate their investment is a very significant issue. Financial subsidies are known by the majority of the people to be one of the most important drivers in renewable energy expansion and one of the main reasons which result in the development of any industry. In this paper, we pr...
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