Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí sinh học đề tài : The International Classification of Functioning as an explanatory model of health after distal radius fracture: A cohort study
Tuyển tập các báo cáo nghiên cứu khoa học ngành y học tạp chí Medical Sciences dành cho các bạn sinh viên ngành y tham khảo đề tài: Multivariate explanatory model for sporadic carcinoma of the colon in Dukes’ stages I and IIa...
It has previously been assumed in the psycholinguistic literature that ﬁnite-state models of language are crucially limited in their explanatory power by the locality of the probability distribution and the narrow scope of information used by the model. We show that a simple computational model (a bigram part-of-speech tagger based on the design used by Corley and Crocker (2000)) makes correct predictions on processing difﬁculty observed in a wide range of empirical sentence processing data. ...
2 Features of marketing research data. The purpose of quantitative models is to summarize marketing research data such that useful conclusions can be drawn. Typically the conclusions concern the impact of explanatory variables on a relevant marketing variable, where we focus only on revealed preference data.
The objective of this study is to develop an early‐warning system (EWS) for identifying
systemic banking risk, which will give policymakers and supervisors time to prevent or mitigate a
potential financial crisis. It is important to forecast—and perhaps to alleviate—the pressures that
lead to systemic crises, which are economically and socially costly and which require significant
time to reverse (Honohan et al., 2003). The current U.S.
This volume consists of an introduction and two groups of essays by Paul M. Postal, each with a connecting theme. The first, positive group of papers, contains five previously unpublished studies of English syntax. These include a long study of so-called "locative inversion," two investigations related to raising to non-subject status, an argument for the existence of a hitherto ignored nominal grammatical category and a study of vulgar negative polarity items. Each investigation of specific English details is argued to have significant theoretical consequences....
Most people take the process of coping for granted as they go about their daily activities. In many ways, coping is like breathing, an automatic process requiring no apparent effort. However, when people face truly threatening events--what psychologists call stressors--they become acutely aware of the coping process and respond by consciously applying their day-to-day coping skills. Coping is a fundamental psychological process, and people's skills are commensurately sophisticated. This volume builds on people's strengths and emphasizes their role as positive copers.
This book is based on the Machette Lectures, delivered at the University
of Ohio, Athens OH in March 1998. It gives me great pleasure to
acknowledge the generous support of the Machette Foundation for the
lecture series and its subsequent publication. I am particularly grateful to
the Philosophy Department of Ohio University at Athens OH for invit-
ing me and for providing such a rewarding and stimulating environment
in which to do philosophy. My special thanks to James Petrik, Donald
Borchert and Albert Mosley for managing the executive side of the visit
But what does knowing about a culture’s explanatory models have to do with getting your
organization’s message to a hard-to-reach audience? Everything, if your message is about health-
related beliefs and behaviors. Often, we try to educate or to convince people to act a certain way
using our explanatory models, instead of theirs. If you want to help a community improve its
health, you need to understand the way its community members think.
Many current approaches to statistical language modeling rely on independence a.~sumptions 1)etween the different explanatory variables. This results in models which are computationally simple, but which only model the main effects of the explanatory variables oil the response variable. This paper presents an argmnent in favor of a statistical approach that also models the interactions between the explanatory variables. The argument rests on empirical evidence from two series of experiments concerning automatic ambiguity resolution. ...
Chapter 4 - Further development and analysis of the classical linear regression model. In this chapter, you will learn how to: Construct models with more than one explanatory variable, test multiple hypotheses using an F-test, determine how well a model fits the data, form a restricted regression, derive the OLS parameter and standard error estimators using matrix algebra, estimate multiple regression models and test multiple hypotheses in EViews.
Metagrammaticai formalisms that combine context-free phrase structure rules and metarules (MPS grammars) allow concise statement of generalizations about the syntax of natural languages. Unconstrained MPS grammars, tmfortunately, are not cornputationally "safe." We evaluate several proposals for constraining them, basing our amae~ment on computational tractability and explanatory adequacy. We show that none of them satisfies both criteria, and suggest new directions for research on alternative metagrammatical formalisms. ...
While the stochastic volatility (SV) generalization has been shown to
improve the explanatory power over the Black-Scholes model, empirical
implications of SV models on option pricing have not yet been adequately
tested. The purpose of this paper is to ﬁrst estimate a multivariate SV
model using the efﬁcient method of moments (EMM) technique from
observations of underlying state variables and then investigate the respective
effect of stochastic interest rates, systematic volatility and idiosyncratic
volatility on option prices....
Multiple regression is the extension of simple regression, to take account of more than one
independent variable X. In multiple regression, we study the relationship between Y and a number of
explanatory variable (X1, X2, …, Xk). The model we assume is as follows:
Yi = β0 + β1X1 + β2X2 + … + βkXk + ei
Take the Pretest, Mode! Test 1 in Chapter 2 and check your answers using the Explanatory or Example Answers and Audio Scripts for Model Tests in Chapter 7. Which sections o( the TOEFL were easier for you? Which were more difficult? Plan to spend more time on the sec-tions on which you received lower scores.
After you finish the work in Chapter 3, you will be ready to check your progress. Take the first Progress Test, Model Test 2 in Chapter 4 and check your answers using the Explanatory or Example Answers in Chapter 7. You should begin to see how the academic skills are used on the new TOEFL® iBT
Generalized Method of Moments and Minimum Distance Estimation
In Chapter 8 we saw how the generalized method of moments (GMM) approach to estimation can be applied to multiple-equation linear models, including systems of equations, with exogenous or endogenous explanatory variables, and to panel data models.
Basic Linear Unobserved E¤ects Panel Data Models
In Chapter 7 we covered a class of linear panel data models where, at a minimum, the error in each time period was assumed to be uncorrelated with the explanatory variables in the same time period. For certain panel data applications this assumption is too strong.
Chapter 6 Nonlinear Regression
Up to this point, we have discussed only linear regression models. For each observation t of any regression model, there is an information set Ωt and a suitably chosen vector Xt of explanatory variables that belong to Ωt .
The last two explanatory variables are control variables, while the remaining
variables are the corporate governance variables that we discussed in Section
VA. As discussed in Section II, the signs of most of these variables are
empirical issues, so we use the observed signs to interpret our results.
The top section of Table 7 shows estimates of four variants of equation
(6) for the full sample.