Variance reduction methods for simulation of densities on Wiener space

We develop a general error analysis framework for the Monte Carlo simulationof densities for functionals in Wiener space. We also study variancereduction methods with the help of Malliavin derivatives. For this, wegive some general heuristic principles which are applied to diffusionprocesses. A comparison with kernel density estimates is made.

Duality in mean-variance frontiers with conditioning information

Portfolio and stochastic discount factor (SDF) frontiers are usually regarded as dual objects, and researchers sometimes use one to answer questions about the other. However, the introduction of conditioning information and active portfolio strategies alters this relationship. For instance, the unconditional portfolio frontier in Hansen and Richard (1987) is not dual to the unconditional SDF frontier in Gallant, Hansen and Tauchen (1990). We characterise the dual objects to those frontiers, and relate them to the frontiers generated with managed portfolios, which are commonly used in empirical work. We also study the implications of a safe asset and other special cases.

Sample size and statistical power in the hierarchical analysis of variance: applications in morphometry of the nervous system.

Analysis of variance is commonly used in morphometry in order to ascertain differences in parameters between several populations. Failure to detect significant differences between populations (type II error) may be due to suboptimal sampling and lead to erroneous conclusions; the concept of statistical power allows one to avoid such failures by means of an adequate sampling. Several examples are given in the morphometry of the nervous system, showing the use of the power of a hierarchical analysis of variance test for the choice of appropriate sample and subsample sizes. In the first case chosen, neuronal densities in the human visual cortex, we find the number of observations to be of little effect. For dendritic spine densities in the visual cortex of mice and humans, the effect is somewhat larger. A substantial effect is shown in our last example, dendritic segmental lengths in monkey lateral geniculate nucleus. It is in the nature of the hierarchical model that sample size is always more important than subsample size. The relative weight to be attributed to subsample size thus depends on the relative magnitude of the between observations variance compared to the between individuals variance.

The mean-variance model from the inverse of the variance-covariance matrix

En este artículo, a partir de la inversa de la matriz de varianzas y covarianzas se obtiene el modelo Esperanza-Varianza de Markowitz siguiendo un camino más corto y matemáticamente riguroso. También se obtiene la ecuación de equilibrio del CAPM de Sharpe.

Effects of common origin and common rearing environment on variance in ectoparasite load and phenotype of nestling Alpine swifts

Knowledge of the quantitative genetics of resistance to parasitism is key to appraise host evolutionary responses to parasite selection. Here, we studied effects of common origin (i.e. genetic and pre-hatching parental effects) and common rearing environment (i.e. post-hatching parental effects and other environment effects) on variance in ectoparasite load in nestling Alpine swifts (Apus melba). This colonial bird is intensely parasitized by blood sucking louse-flies that impair nestling development and survival. By cross-fostering half of the hatchlings between pairs of nests, we show strong significant effect of common rearing environment on variance (90.7% in 2002 and 90.9% in 2003) in the number of louse-flies per nestling and no significant effect of common origin on variance in the number of louse-flies per nestling. In contrast, significant effects of common origin were found for all the nestling morphological traits (i.e. body mass, wing length, tail length, fork length and sternum length) under investigation. Hence, our study suggests that genetic and pre-hatching parental effects play little role in the distribution of parasites among nestling Alpine swifts, and thus that nestlings have only limited scope for evolutionary responses against parasites. Our results highlight the need to take into consideration environmental factors, including the evolution of post-hatching parental effects such as nest sanitation, in our understanding of host-parasite relationships.

The mean-variance model from the inverse of the variance-covariance matrix

En este artículo, a partir de la inversa de la matriz de varianzas y covarianzas se obtiene el modelo Esperanza-Varianza de Markowitz siguiendo un camino más corto y matemáticamente riguroso. También se obtiene la ecuación de equilibrio del CAPM de Sharpe.

The evolution and consequences of sex-specific reproductive variance.

Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction.

Natural selection on fecundity variance in subdivided populations: kin selection meets bet hedging.

In a series of seminal articles in 1974, 1975, and 1977, J. H. Gillespie challenged the notion that the "fittest" individuals are those that produce on average the highest number of offspring. He showed that in small populations, the variance in fecundity can determine fitness as much as mean fecundity. One likely reason why Gillespie's concept of within-generation bet hedging has been largely ignored is the general consensus that natural populations are of large size. As a consequence, essentially no work has investigated the role of the fecundity variance on the evolutionary stable state of life-history strategies. While typically large, natural populations also tend to be subdivided in local demes connected by migration. Here, we integrate Gillespie's measure of selection for within-generation bet hedging into the inclusive fitness and game theoretic measure of selection for structured populations. The resulting framework demonstrates that selection against high variance in offspring number is a potent force in large, but structured populations. More generally, the results highlight that variance in offspring number will directly affect various life-history strategies, especially those involving kin interaction. The selective pressures on three key traits are directly investigated here, namely within-generation bet hedging, helping behaviors, and the evolutionary stable dispersal rate. The evolutionary dynamics of all three traits are markedly affected by variance in offspring number, although to a different extent and under different demographic conditions.

Analysis of experiments in square lattice with emphasis on variance components. i. Individual analysis

This paper focused on four alternatives of analysis of experiments in square lattice as far as the estimation of variance components and some genetic parameters are concerned: 1) intra-block analysis with adjusted treatment and blocks within unadjusted repetitions; 2) lattice analysis as complete randomized blocks; 3) intrablock analysis with unadjusted treatment and blocks within adjusted repetitions; 4) lattice analysis as complete randomized blocks, by utilizing the adjusted means of treatments, obtained from the analysis with recovery of interblock information, having as mean square of the error the mean effective variance of this same analysis with recovery of inter-block information. For the four alternatives of analysis, the estimators and estimates were obtained for the variance components and heritability coefficients. The classification of material was also studied. The present study suggests that for each experiment and depending of the objectives of the analysis, one should observe which alternative of analysis is preferable, mainly in cases where a negative estimate is obtained for the variance component due to effects of blocks within adjusted repetitions.

Analysis of variance of primary data on plant growth analysis

Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.

Covariance Matrix Estimation and Mean-Variance Optimization in application to International Diversification

Tutkimus keskittyy kansainväliseen hajauttamiseen suomalaisen sijoittajan näkökulmasta. Tutkimuksen toinen tavoite on selvittää tehostavatko uudet kovarianssimatriisiestimaattorit minimivarianssiportfolion optimointiprosessia. Tavallisen otoskovarianssimatriisin lisäksi optimoinnissa käytetään kahta kutistusestimaattoria ja joustavaa monimuuttuja-GARCH(1,1)-mallia. Tutkimusaineisto koostuu Dow Jonesin toimialaindekseistä ja OMX-H:n portfolioindeksistä. Kansainvälinen hajautusstrategia on toteutettu käyttäen toimialalähestymistapaa ja portfoliota optimoidaan käyttäen kahtatoista komponenttia. Tutkimusaieisto kattaa vuodet 1996-2005 eli 120 kuukausittaista havaintoa. Muodostettujen portfolioiden suorituskykyä mitataan Sharpen indeksillä. Tutkimustulosten mukaan kansainvälisesti hajautettujen investointien ja kotimaisen portfolion riskikorjattujen tuottojen välillä ei ole tilastollisesti merkitsevää eroa. Myöskään uusien kovarianssimatriisiestimaattoreiden käytöstä ei synnytilastollisesti merkitsevää lisäarvoa verrattuna otoskovarianssimatrisiin perustuvaan portfolion optimointiin.

The influence of the quality of government institutions on entrepreneurial motivation: exploring the variance across countries

Despite the increasing understanding of the relationships between institutions and entrepreneurship, the influence of the quality of government institutions on entrepreneurship is less addressed. This paper focuses on this critical determinant of entrepreneurship in developing and developed countries. Drawing from institutional theory we hypothesize and empirically assess the role of the quality of institutions in entrepreneurial activity. We examine how the quality of government institutions influences the rate of necessity-based entrepreneurial activity across countries and over time by using a cross-sectional time-series approach on data from the Global Entrepreneurship Monitor (GEM) database covering the years 2001–2011. Our results suggest that higher economic development associated with better quality of institutions reduces the prevalence of necessity-based entrepreneurship. Our findings imply that developing countries must rationally organize their functions, and seek to remove unnecessary barriers, decrease political instability, and controls that hamper entrepreneurial activity

Ecological and physiological variance in T-cell mediated immune response in Cory's shearwaters

T-cell mediated immune response (CMI) hasbeen widely studied in relation to individual andfitness components in birds. However, few studieshave simultaneously examined individual and socialfactors and habitat-mediated variance in theimmunity of chicks and adults from the samepopulation and in the same breeding season. Weinvestigated ecological and physiological variancein CMI of male and female nestlings and adults in abreeding population of Cory's Shearwaters(Calonectrisdiomedea) in theMediterranean Sea. Explanatory variables includedindividual traits (body condition, carbon andnitrogen stable isotope ratios, plasma totalproteins, triglycerides, uric acid, osmolarity,β-hydroxy-butyrate, erythrocyte meancorpuscular diameter, hematocrit, andhemoglobin) and burrow traits(temperature, isolation, and physicalstructure). During incubation, immune responseof adult males was significantly greater than thatof females. Nestlings exhibited a lower immuneresponse than adults. Ecological and physiologicalfactors affecting immune response differed betweenadults and nestlings. General linear models showedthat immune response in adult males was positivelyassociated with burrow isolation, suggesting thatmales breeding at higher densities suffer immunesystem suppression. In contrast, immune response inchicks was positively associated with bodycondition and plasma triglyceride levels.Therefore, adult immune response appears to beassociated with social stress, whereas a trade-offbetween immune function and fasting capability mayexist for nestlings. Our results, and those fromprevious studies, provide support for anasymmetrical influence of ecological andphysiological factors on the health of differentage and sex groups within a population, and for theimportance of simultaneously considering individualand population characteristics in intraspecificstudies of immune response.