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Spline Regression Models Quantitative Applications In The ...

Spline Regression Models Quantitative Applications In The ...

MONOGRAPHS 1999 WAHBA G SPLINE MODELS FOR OBSERVATIONAL DATA CBMS NSF REGIONAL CONFERENCE SERIES IN APPLIED MATHEMATICS 1990'' quantitative applications in the social sciences June 2nd, 2020 - the classical linear regression model has been part and parcel of a quantitative social scientist s methodology for at least four decades the quantitative applications in the social sciences series has ...

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Tax Policy, Foreign Direct Investment and Spillover Effects

Tax Policy, Foreign Direct Investment and Spillover Effects

spillover effects on the level of FDI in neighboring countries. As emphasized by Lesage and Pace (2009), ignoring the spatial interactions in regression models (OLS, panel data, etc.) can not only bias the standard deviations but can also have an impact on the value of the estimates. This paper takes spillover effects into account by using a spatial econometrics approach. The remainder of the ...

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RECOGNITION OF PHONEMES AND WORDS IN SINGING Annamaria ...

RECOGNITION OF PHONEMES AND WORDS IN SINGING Annamaria ...

Using two steps of constrained maximum likelihood linear re-gression (MLLR), the models were adapted to singing voice. In the ?rst step, 8 regression classes were de?ned based on broad ph onetic classes [9]: monophtongs, diphtongs, approximants, nasals, frica- tives, plosives, affricates. In the second adaptation step, the base classes for adaptation were determined by clustering the ...

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Linear Regression Analysis for Survey Data

Linear Regression Analysis for Survey Data

From Simple to Multiple Regression 9 • Simple linear regression: One Y variable and one X variable (y i=? 0+ ? 1x i+?) • Multiple regression: One Y variable and multiple X variables – Like simple regression, we’re trying to model how Y depends on X – Only now we are building models where Y may depend on many Xs y i=? 0+ ? 1x 1i + … + ? kx ki +?. Using Multiple Regression to ...

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Multivariate ordinal regression models: an analysis of ...

Multivariate ordinal regression models: an analysis of ...

Credit ratings are ordinal rankings of credit risk, i.e., the risk of a ?rm not being able to meet its ?nancial obligations. Such credit ratings can be either produced by banks which use internal rating models or are provided by credit ratings agencies (CRAs). CRAs like Standard and Poor’s (S&P), Moody’s and Fitch play a signi?cant ...

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Stata Press Publication - Indiana University

Stata Press Publication - Indiana University

new to Stata are likely to find that this chapter has more detail than you need initially. As we proceed, we suggest which sections one may wish to only skim on first reading. Part II covers regression models for a different types of outcomes. Chapters 5 and 6: Models for binary outcomes begins with an overview of how the binary logit and probit models are derived and how they can be fitted ...

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Encog: Library of Interchangeable Machine Learning Models ...

Encog: Library of Interchangeable Machine Learning Models ...

mentations. The Encog framework supports machine learning models with multiple training algorithms. These models are listed here: Adaline, Feedforward, Hop eld, PNN/GRNN, RBF & NEAT neural networks generalized linear regression (GLM) genetic programming (tree-based) k-means clustering k-nearest neighbors linear regression self-organizing map (SOM)

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Making regression tables from stored estimates

Making regression tables from stored estimates

Statistical packages are usually very good at estimating all kinds of regression mod-els, but they are rather poor at keeping the results for those models organized and/or processing them for publication. This is a real problem because gathering the rele-vant ?gures by hand from the large amount of statistical output usually produced and arranging the results in clear and presentable tables ...

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Climate, Birth Weight, and Agricultural Livelihoods in ...

Climate, Birth Weight, and Agricultural Livelihoods in ...

Mali and Kenya in relation to the local agricultural specialization. Methods. We combined health and sociodemographic data from the Demographic HealthSurveysforKenya(2008and2014)andMali(2006and2012)withdetaileddataon precipitation, temperature, and vegetation. We analyzed the association between cli-mate variability and birth weight by using multilevel regression models for the most common ...

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Predicting Bank Loan Recovery Rates in a Mixed Continuous ...

Predicting Bank Loan Recovery Rates in a Mixed Continuous ...

Predicting Bank Loan Recovery Rates in a Mixed Continuous-Discrete model. Raffaella Calabrese I propose to consider the recovery rate as a mixed random variable, obtained as the mixture of a Bernoulli and a beta random variables. I estimate the mixture weights and the Bernoulli parameter by two logistic regression models. For the recovery rates belonging to the interval (0,1), I model, jointly ...

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Interference of annual sowthistle (Sonchus oleraceus) in wheat

Interference of annual sowthistle (Sonchus oleraceus) in wheat

A Walter-Lieth climate diagram was prepared using the CLIMATOL package (R Development Core Team 2018). To assess the relationship between weed density and crop yield loss, several commonly used models were compared using the Akaike information criterion (AIC) (Table 1). The model with the lowest AIC was a two parameter modified exponential decay regression model: g ¼ a 1 exp ?1 in) a ...

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