A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters

Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.

Inequalities for a new data-based method for selecting nonparametric density estimates

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provideexplicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate,and study in particular the connection between the richness of the classof density estimates and the performance bound. For example, our methodallows one to pick the bandwidth and kernel order in the kernel estimatesimultaneously and still assure that for {\it all densities}, the $L_1$error of the corresponding kernel estimate is not larger than aboutthree times the error of the estimate with the optimal smoothing factor and kernel plus a constant times $\sqrt{\log n/n}$, where $n$ is the sample size, and the constant only depends on the complexity of the family of kernels used in the estimate. Further applications include multivariate kernel estimates, transformed kernel estimates, and variablekernel estimates.

A model of collateral, investment and adverse selection

This paper characterizes the relationship between entrepreneurial wealth and aggregate investmentunder adverse selection. Its main finding is that such a relationship need not bemonotonic. In particular, three results emerge from the analysis: (i) pooling equilibria, in whichinvestment is independent of entrepreneurial wealth, are more likely to arise when entrepreneurialwealth is relatively low; (ii) separating equilibria, in which investment is increasing inentrepreneurial wealth, are most likely to arise when entrepreneurial wealth is relatively highand; (iii) for a given interest rate, an increase in entrepreneurial wealth may generate a discontinuousfall in investment.

The size and distribution of donations: Effects of numbers of potential recipients

Whereas much literature exists on choice overload, little is known about effects of numbers of alternatives in donation decisions. How do these affect both the size and distribution of donations? We hypothesize that donations are affected by the reputation of recipients and increase with their number, albeit at a decreasing rate. Allocations to recipients reflect different concepts of fairness equity and equality. Both may be employed but, since they differ in cognitive and emotional costs, numbers of recipients are important. Using a cognitive (emotional) argument, distributions become more uniform (skewed) as numbers increase. In a survey, respondents indicated how they would donate lottery winnings of 50 Euros. Results indicated that more was donated to NGO s that respondents knew better. Second, total donations increased with the number of recipients albeit at a decreasing rate. Third, distributions of donations became more skewed as numbers increased. We comment on theoretical and practical implications.

Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical {\sc vc} dimension, empirical {\sc vc} entropy, andmargin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

Systematic study of the static electrical properties of the CO molecule: influence of the basis set size and correlation energy

The influence of the basis set size and the correlation energy in the static electrical properties of the CO molecule is assessed. In particular, we have studied both the nuclear relaxation and the vibrational contributions to the static molecular electrical properties, the vibrational Stark effect (VSE) and the vibrational intensity effect (VIE). From a mathematical point of view, when a static and uniform electric field is applied to a molecule, the energy of this system can be expressed in terms of a double power series with respect to the bond length and to the field strength. From the power series expansion of the potential energy, field-dependent expressions for the equilibrium geometry, for the potential energy and for the force constant are obtained. The nuclear relaxation and vibrational contributions to the molecular electrical properties are analyzed in terms of the derivatives of the electronic molecular properties. In general, the results presented show that accurate inclusion of the correlation energy and large basis sets are needed to calculate the molecular electrical properties and their derivatives with respect to either nuclear displacements or/and field strength. With respect to experimental data, the calculated power series coefficients are overestimated by the SCF, CISD, and QCISD methods. On the contrary, perturbation methods (MP2 and MP4) tend to underestimate them. In average and using the 6-311 + G(3df) basis set and for the CO molecule, the nuclear relaxation and the vibrational contributions to the molecular electrical properties amount to 11.7%, 3.3%, and 69.7% of the purely electronic μ, α, and β values, respectively

Revised NEO personality inventory normative data for catalan police officer selection: preliminary study

El Servei d'Avaluació, Seguiment i Selecció de l'ISPC han elaborat un estudi sobre el perfil de personalitat dels aspirants al Curs de Formació bàsica per policies, que es va presentar a l'International Society for the Study of Individual Differences Meeting celebrat al CosmoCaixa de Barcelona i que organitzen conjuntament l’Associació Iberoamericana per a la recerca de les diferències individuals i la Universitat de Barcelona. L’estudi, titulat Revised NEO Personality Inventory Normative Data for Catalan police officer selection: A preliminary study, té com a objectiu comparar els perfils de personalitat d’una mostra d’aspirants de l’ISPC amb els resultats d’una mostra d’aspirants a policia dels EUA, publicada en una revista científica de prestigi el mes de febrer passat. Els resultats mostren que els aspirants catalans destaquen per obtenir millors puntuacions en les dimensions de responsabilitat i amabilitat, cosa que indicaria que aquest tret es valora especialment durant el procés de selecció de la policia de Catalunya; en altres característiques de la personalitat les dues mostres obtenen resultats similars. Els trets característics del perfil del policia català seria el de persones estables emocionalment, poc impulsives, amb capacitat per gestionar l’estrés, orientades a les persones, agradables, sociables, responsables, disciplinades i cauteloses. Enllaç a: International Society for the Study of Individual Differences Meeting :http://www.issid.org/conferences/ISSID2013/ISSIDconference2013.html