Pamela Paxton,
John R. Hipp &
Sandra Marquart-Pyatt
(2011)
A clear and concise introduction to the estimation and assessment of nonrecursive simultaneous equation models. This unique monograph gives practical advice on the specification and identification of simultaneous equation models, how to assess the quality of the estimates, and how to correctly in...
A clear and concise introduction to the estimation and assessment of nonrecursive simultaneous equation models. This unique monograph gives practical advice on the specification and identification of simultaneous equation models, how to assess the quality of the estimates, and how to correctly in...
While regression analysis traces the dependence of the distribution of a response variable to see if it bears a particular (linear) relationship to one or more of the predictors, nonparametric regression analysis makes minimal assumptions about the form of relationship between the average respons...
While regression analysis traces the dependence of the distribution of a response variable to see if it bears a particular (linear) relationship to one or more of the predictors, nonparametric regression analysis makes minimal assumptions about the form of relationship between the average respons...
Neural networks, adaptive statistical models based on an analogy with the structure of the brain, can be used to estimate the parameters of some population using one (or a few) exemplars at a time. This book introduces readers to the basic models of neural networks and compares and contrasts thes...
Neural networks, adaptive statistical models based on an analogy with the structure of the brain, can be used to estimate the parameters of some population using one (or a few) exemplars at a time. This book introduces readers to the basic models of neural networks and compares and contrasts thes...
When analyzing data, how should the relationship between two or more sets of
observations be described, that is, values of two or more variables, when the
variables are ordinal and not bivariate normal? Aimed at helping the researcher
...
When analyzing data, how should the relationship between two or more sets of
observations be described, that is, values of two or more variables, when the
variables are ordinal and not bivariate normal? Aimed at helping the researcher
...
Through the use of actual research investigations that have appeared in recent social science journals, Gibbons shows the reader the specific methodology and logical rationale for many of the best-known and most frequently used nonparametric methods that are applicable to most small and large sam...
Through the use of actual research investigations that have appeared in recent social science journals, Gibbons shows the reader the specific methodology and logical rationale for many of the best-known and most frequently used nonparametric methods that are applicable to most small and large sam...
Where an assumption of unidirectionality in causal effects is unrealistic,
‘recursive’ models cannot be used, and more complex ‘nonrecursive’ models are
necessary. Unfortunately, many nonrecursive models (unlike recursive models) are
...
Where an assumption of unidirectionality in causal effects is unrealistic,
‘recursive’ models cannot be used, and more complex ‘nonrecursive’ models are
necessary. Unfortunately, many nonrecursive models (unlike recursive models) are
...