USING A LAPLACE APPROXIMATION TO ESTIMATE THE RANDOM COEFFICIENTS LOGIT MODEL BY NONLINEAR LEAST SQUARES*
نویسندگان
چکیده
منابع مشابه
The random coefficients logit model is identified
The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the distribution of random coefficients in the multinomial logit model is nonparametrically identified. Our approach requires variation in product characteristics only locally and does not rely on the special regressors...
متن کاملLeast-squares Approximation of Random Variables by Stochastic Integrals∗
This paper addresses the problem of approximating random variables in terms of sums consisting of a real constant and of a stochastic integral with respect to a given semimartingale X. The criterion is minimization of L−distance, or “least-squares”. This problem has a straightforward and well-known solution when X is a Brownian motion or, more generally, a square-integrable martingale, with res...
متن کاملShape Recognition using the Least Squares Approximation
This paper represents a novel algorithm to represent and recognize two dimensional curve based on its convex hull and the Least-Squared modeling. It combines the advantages of the property of the convex hulls that are particularly suitable for affine matching as they are affine invariant and the geometric properties of a contour that make it more or less identifiable. The description scheme and...
متن کاملLeast-squares approximation by a tree distance
Let T be a tree with vertex set V (T ) = {1, . . . , n} and with a positive weight associated with each edge. The tree distance between i and j is the weight of the ij-path. Given a symmetric, positive real valued function on V (T )×V (T ), we consider the problem of approximating it by a tree distance corresponding to T, by the least-squares method. The problem is solved explicitly when T is a...
متن کاملOn Least Squares Exponential Sum Approximation With Positive Coefficients*
An algorithm is given for finding optimal least squares exponential sum approximations to sampled data subject to the constraint that the coefficients appearing in the exponential sum are positive. The algorithm employs the divided differences of exponentials to overcome certain problems of ill-conditioning and is suitable for data sampled at noninteger times.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Economic Review
سال: 2007
ISSN: 0020-6598
DOI: 10.1111/j.1468-2354.2007.00463.x