Minimum distance estimation of stationary and non-stationary ARFIMA processes

A new parametric minimum distance time-domain estimator for ARFIMA processes is introduced in this paper. The proposed estimator minimizes the sum of squared correlations of residuals obtained after filtering a series through ARFIMA parameters. The estimator iseasy to compute and is consistent and asymptotically normally distributed for fractionallyintegrated (FI) processes with an integration order d strictly greater than -0.75. Therefore, it can be applied to both stationary and non-stationary processes. Deterministic components are also allowed in the DGP. Furthermore, as a by-product, the estimation procedure provides an immediate check on the adequacy of the specified model. This is so because the criterion function, when evaluated at the estimated values, coincides with the Box-Pierce goodness of fit statistic. Empirical applications and Monte-Carlo simulations supporting the analytical results and showing the good performance of the estimator in finite samples are also provided.

Improving small area estimation by combining surveys: new perspectives in regional statistics

A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour Force Survey (EPA) and the Barometer in Spain for our study.

Convergence in panel data: Evidence from the skipping estimation

This paper demonstrates that, unlike what the conventional wisdom says, measurement error biases in panel data estimation of convergence using OLS with fixed effects are huge, not trivial. It does so by way of the "skipping estimation"': taking data from every m years of the sample (where m is an integer greater than or equal to 2), as opposed to every single year. It is shown that the estimated speed of convergence from the OLS with fixed effects is biased upwards by as much as 7 to 15%.

Quantitative estimation of foot-flat and stance phase of gait using foot-worn inertial sensors.

Time periods composing stance phase of gait can be clinically meaningful parameters to reveal differences between normal and pathological gait. This study aimed, first, to describe a novel method for detecting stance and inner-stance temporal events based on foot-worn inertial sensors; second, to extract and validate relevant metrics from those events; and third, to investigate their suitability as clinical outcome for gait evaluations. 42 subjects including healthy subjects and patients before and after surgical treatments for ankle osteoarthritis performed 50-m walking trials while wearing foot-worn inertial sensors and pressure insoles as a reference system. Several hypotheses were evaluated to detect heel-strike, toe-strike, heel-off, and toe-off based on kinematic features. Detected events were compared with the reference system on 3193 gait cycles and showed good accuracy and precision. Absolute and relative stance periods, namely loading response, foot-flat, and push-off were then estimated, validated, and compared statistically between populations. Besides significant differences observed in stance duration, the analysis revealed differing tendencies with notably a shorter foot-flat in healthy subjects. The result indicated which features in inertial sensors' signals should be preferred for detecting precisely and accurately temporal events against a reference standard. The system is suitable for clinical evaluations and provides temporal analysis of gait beyond the common swing/stance decomposition, through a quantitative estimation of inner-stance phases such as foot-flat.

Location of multiple server common service centers or public facilities for minimizing general congestion and travel cost functions

We propose a model and solution methods, for locating a fixed number ofmultiple-server, congestible common service centers or congestible publicfacilities. Locations are chosen so to minimize consumers congestion (orqueuing) and travel costs, considering that all the demand must be served.Customers choose the facilities to which they travel in order to receiveservice at minimum travel and congestion cost. As a proxy for thiscriterion, total travel and waiting costs are minimized. The travel costis a general function of the origin and destination of the demand, whilethe congestion cost is a general function of the number of customers inqueue at the facilities.

Estimates of patient costs related with population morbidity: Can indirect costs affect the results?

A number of health economics works require patient cost estimates as a basic information input.However the accuracy of cost estimates remains in general unspecified. We propose to investigate howthe allocation of indirect costs or overheads can affect the estimation of patient costs in order to allow forimprovements in the analysis of patient costs estimates. Instead of focusing on the costing method, thispaper proposes to highlight changes in variance explained observed when a methodology is chosen. Wecompare three overhead allocation methods for a specific Spanish population adjusted using the ClinicalRisk Groups (CRG), and we obtain different series of full-cost group estimates. As a result, there aresignificant gains in the proportion of the variance explained, depending upon the methodology used.Furthermore, we find that the global amount of variation explained by risk adjustment models dependsmainly on direct costs and is independent of the level of aggregation used in the classification system.

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.

Fitness cost of resistance to Bacillus thuringiensis in velvetbean caterpillar Anticarsia gemmatalis Hübner (Lepidoptera, Noctuidae)

Selection pressure to obtain resistant genotypes can result in fitness cost. In this study, we report the effects of the selection pressure of a commercial formulation of Bacillus thuringiensis on biological aspects of a Dipel-resistant strain of velvetbean caterpillar, Anticarsia gemmatalis Hübner. Comparisons of Dipel-resistant and susceptible individuals revealed significant differences in pupal weight and larval development time. Both strains (Dipel-resistant and susceptible) were susceptible to Cry1Ac toxin expressed in foliar cotton tissues. Resistant and susceptible strains showed low survival rates of 22.5% and 51.2%, respectively, when fed with Greene diet containing Bt-cotton. Larvae bioassayed after three laboratory generations presented lower survival and less instar numbers than individuals maintained in the laboratory for more than 144 generations. Pupal weight was 9.4% lower and larval development time was 1.9 days longer in the resistant population than in the susceptible strain. Other parameters, such as duration of pupal stage, adult longevity, number of eggs per female, oviposition period, and egg fertility, remained unaffected.

Non-stationary job search when jobs are not forever: A structural estimation

This paper considers a job search model where the environment is notstationary along the unemployment spell and where jobs do not lastforever. Under this circumstance, reservation wages can be lower thanwithout separations, as in a stationary environment, but they can alsobe initially higher because of the non-stationarity of the model. Moreover,the time-dependence of reservation wages is stronger than with noseparations. The model is estimated structurally using Spanish data forthe period 1985-1996. The main finding is that, although the decrease inreservation wages is the main determinant of the change in the exit ratefrom unemployment for the first four months, later on the only effect comesfrom the job offer arrival rate, given that acceptance probabilities areroughly equal to one.

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.

Energetic cost of digging behavior in workers of the leaf-cutting ant Atta sexdens (Fabricius)

Energetic cost of digging behavior in workers of the leaf-cutting ant Atta sexdens (Fabricius). During nest excavation, leaf-cutting ant workers undergo reduction in their body reserve, particularly carbohydrates. In order to estimate the energetic cost of digging, groups of 30 workers of the leaf-cutting ant Atta sexdens were sealed in a hermetic chamber for 24, 48 and 72 hours, with and without soil for digging, and had the CO2 concentration measured using respirometric chambers as well as volume of soil excavated (g). As expected, the worker groups that carried out soil excavation expelled more carbon dioxide than the groups that did not excavate. Therefore, a worker with body mass of 9.65 ± 1.50 mg dug in average 0.85 ± 0.27 g of soil for 24 hours, consuming ca. 0.58 ± 0.23 J. In this study, we calculate that the energetic cost of excavation per worker per day in the experimental set-up was ca. 0.58 J.

Energetic and metabolic cost of growth in Gambian infants.

The aim of the study was to measure the energy used for growth of healthy fullterm and breast-fed Gambian infants. The weight gain (WG) of 14 infants (mean age +/- SEM 17 +/- 1 d, weight 3.581 +/- 0.105 kg) was measured over a 2-week period; the energy intake (EI) from breast milk was assessed for 24 h in the middle of the study period by weighing the infant before and after each breast-feed. On the same day, sleeping energy expenditure (SEE) and respiratory quotient (RQ) were measured for 30 min on five occasions through the 24-h period. EI averaged 502 +/- 25 kJ/kg.d, and SEE 230 +/- 6 kJ/kg.d; thus, an average of 272 kJ/kg.d were available for physical activity and the energy stored for growth. The total energy spent by infants while sleeping and for periods of physical activity was calculated to be 1.7 x SEE. The mean RQ measured on five occasions averaged 0.879 +/- 0.009. SEE was correlated with WG (r = 0.747, P less than 0.005), with a slope of the regression line of 5.5 kJ/g; this value can be considered as an estimate of the energy spent for new tissue synthesis in the resting infant. The efficiency of weight gain was lower in this study (67%) than in studies conducted on fast-growing preterm infants or children recovering from malnutrition.

Biomass estimation of Triplectides egleri Sattler (Trichoptera, Leptoceridae) in a stream at Ducke Reserve, Central Amazonia

ABSTRACT Biomass is a fundamental measure for understanding the structure and functioning (e.g. fluxes of energy and nutrients in the food chain) of aquatic ecosystems. We aim to provide predictive models to estimate the biomass of Triplectides egleri Sattler, 1963, in a stream in Central Amazonia, based on body and case dimensions. We used body length, head-capsule width, interocular distance and case length and width to derive biomass estimations. Linear, exponential and power regression models were used to assess the relationship between biomass and body or case dimensions. All regression models used in the biomass estimation of T. egleri were significant. The best fit between biomass and body or case dimensions was obtained using the power model, followed by the exponential and linear models. Body length provided the best estimate of biomass. However, the dimensions of sclerotized structures (interocular distance and head-capsule width) also provided good biomass predictions, and may be useful in estimating biomass of preserved and/or damaged material. Case width was the dimension of the case that provided the best estimate of biomass. Despite the low relation, case width may be useful in studies that require low stress on individuals.

Scaling of semivariograms and the kriging estimation of field-measured properties

Two methods were evaluated for scaling a set of semivariograms into a unified function for kriging estimation of field-measured properties. Scaling is performed using sample variances and sills of individual semivariograms as scale factors. Theoretical developments show that kriging weights are independent of the scaling factor which appears simply as a constant multiplying both sides of the kriging equations. The scaling techniques were applied to four sets of semivariograms representing spatial scales of 30 x 30 m to 600 x 900 km. Experimental semivariograms in each set successfully coalesced into a single curve by variances and sills of individual semivariograms. To evaluate the scaling techniques, kriged estimates derived from scaled semivariogram models were compared with those derived from unscaled models. Differences in kriged estimates of the order of 5% were found for the cases in which the scaling technique was not successful in coalescing the individual semivariograms, which also means that the spatial variability of these properties is different. The proposed scaling techniques enhance interpretation of semivariograms when a variety of measurements are made at the same location. They also reduce computational times for kriging estimations because kriging weights only need to be calculated for one variable. Weights remain unchanged for all other variables in the data set whose semivariograms are scaled.

The cost of inappropriateness of coagulation testing [I costi dell'inappropriatezza in coagulazione]

Background. Laboratory utilization has steadily increased with a corresponding increase in overall costs; several authors have attempted to measure the impact of inappropriateness on clinical outcomes but data are insufficient. The aim of the study is to assess the cost of inappropriateness of test-ordering behaviour for second-level coagulation tests (hemorrhagic diathesisand thrombophilia). Methods. We reviewed all second-level coagulation testrequests received by our department during a six months period. Clinicians must fill out a specific order form for these kind of tests, containing all informations deemed necessary for the laboratory specialist to evaluatethe appropriateness of the request. We identified all inappropriate requests and counted the numbers and types of all coagulation tests that were not performed during the period. An analysis of the laboratory activity costs was done in order to calculate the global costof each test in our department and to estimate the savings achieved. Results. On a total of 1664 second-level coagulationtest requests, we estimated 150 as completely inappropriate. We found an overall of 295 inappropriate testswhich were not performed. This resulted in an economic saving of 20.000 euro in 6 months. Conclusions. The analysis of cost of our intervention shows the urgent need for a definite and sustained reduction in inappropriate requests of second-level coagulation tests. Even though we estimated only the economic aspect of inappropriate testing, this is also associated with the overuse of diagnostic tests which entailsthe risk of generating erroneous results with potentialnegative consequences on patients' health.