884 resultados para effort estimation
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Objective: Single port laparoscopy andNOTES aim at decreasing the number¦of trocars, at a price of increased technical difficulty and cost, without until now¦any proof of benefit for the patient.Morbidity related to 5 mm trocar sites (TS)¦is claimed to be low, but there are no good quality data on this topic. The aim¦of the present prospective study is to measure the morbidity and overall specific¦impact related to the 5 mm TS and compare them to larger TS.¦Methods:Wecollected prospectively data on 300 consecutive patients operated¦by laparoscopy in our institution between 2009 and 2010. Pain, morbidity,¦cosmetic, and overall patient discomfort were assessed specifically for each¦TS, using standardized questionnaires, at 3 time points: at discharge from¦the hospital, at 1 month and at 6 months after surgery. Results were compared¦between 5 mmand larger TS (10 mm, 12 mmand 15 mm).Trocar sites replaced¦by a minilaparotomy or a stoma were excluded from analysis. In this study we¦present the short-term results.¦Results: Three-hundred patients (mean age 47·5, women 55%) were operated¦with 1074 TS of which 477(44%) were 5 mm TS. Indication to laparoscopy was¦cholecystectomy (31·3%), appendectomy (26·6%), upper GI surgery (16·3%),¦colon resection (13·3%) or other (12·3%). Follow-up at 1 month was completed¦in 90%.¦The 5 mm TS had an infection rate of 0·2%, and a hematoma rate of 1·7%.¦VAS pain scores at the 5mm TS were ≤3 in 91·6% at rest and in 75·9% upon¦effort at discharge, and in 97% at 1 month. Median patient scar assessment¦score (PSAS) of the 5 mm TS at 1 month was 6 (IQR: 2-9) out of 60 (0 =¦best score). Overall discomfort of the 5 mm TS in a VAS scale was 0 in 77%¦and ≤3 in 95% of patients at 1 month. Morbidity, pain assessments, PSAS, and¦overall discomfort scores were all significantly better for 5 mm TS compared to¦larger TS.¦Conclusion: Morbidity, pain, cosmetic impact and overall patient's discomfort¦related to a 5 mm trocar site is extremely low. For this reason, any potential¦advantage related to omitting 5 mm trocars to perform the same type of surgery¦will be difficult to demonstrate.
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This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.
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In this article we propose using small area estimators to improve the estimatesof both the small and large area parameters. When the objective is to estimateparameters at both levels accurately, optimality is achieved by a mixed sampledesign of fixed and proportional allocations. In the mixed sample design, oncea sample size has been determined, one fraction of it is distributedproportionally among the different small areas while the rest is evenlydistributed among them. We use Monte Carlo simulations to assess theperformance of the direct estimator and two composite covariant-freesmall area estimators, for different sample sizes and different sampledistributions. Performance is measured in terms of Mean Squared Errors(MSE) of both small and large area parameters. It is found that the adoptionof small area composite estimators open the possibility of 1) reducingsample size when precision is given, or 2) improving precision for a givensample size.
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The present work aims at knowing the faunal composition of drosophilids in forest areas of southern Brazil. Besides, estimation of species richness for this fauna is briefly discussed. The sampling were carried out in three well-preserved areas of the Atlantic Rain Forest in the State of Santa Catarina. In this study, 136,931 specimens were captured and 96.6% of them were identified in the specific level. The observed species richness (153 species) is the largest that has been registered in faunal inventories conducted in Brazil. Sixty-three of the captured species did not fit to the available descriptions, and we believe that most of them are non-described species. The incidence-based estimators tended to give rise to the largest richness estimates while the abundance based give rise to the smallest ones. Such estimators suggest the presence from 172.28 to 220.65 species in the studied area. Based on these values, from 69.35 to 88.81% of the expected species richness were sampled. We suggest that the large richness recorded in this study is a consequence of the large sampling effort, the capture method, recent advances in the taxonomy of drosophilids, the high preservation level and the large extension of the sampled fragment and the high complexity of the Atlantic Rain forest. Finally, our data set suggest that the employment of estimators of richness for drosophilid assemblages is useful but it requires caution.
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Previous indirect evidence suggests that impulses towards pro-socialbehavior are diminished when an external authority is responsiblefor an outcome. The responsibility-alleviation effect states that ashift of responsibility to an external authority dampens internalimpulses toward honesty, loyalty, or generosity. In a gift-exchangeexperiment, we find that subjects respond with more generosity(higher effort) when a wage is determined by a random process thanwhen it is assigned by a third party, indicating that even a slightshift in perceived responsibility for the final payoffs can changebehavior. Responsibility-alleviation is a factor in economicenvironments featuring substantial personal interaction.
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We revisit the debt overhang question. We first use non-parametric techniques to isolate a panel of countries on the downward sloping section of a debt Laffer curve. In particular, overhang countries are ones where a threshold level of debt is reached in sample, beyond which (initial) debt ends up lowering (subsequent)growth. On average, significantly negative coefficients appear when debt face value reaches 60 percent of GDP or 200 percent of exports, and when its present value reaches 40 percent of GDP or 140 percent of exports. Second, we depart from reduced form growth regressions and perform direct tests of the theory on the thus selected sample of overhang countries. In the spirit of event studies, we ask whether, as overhang level of debt is reached: (i)investment falls precipitously as it should when it becomes optimal to default, (ii) economic policy deteriorates observably, as it should when debt contracts become unable to elicit effort on the part of the debtor, and (iii) the terms of borrowing worsen noticeably, as they should when it becomes optimal for creditors to pre-empt default and exact punitive interest rates. We find a systematic response of investment, particularly when property rights are weakly enforced, some worsening of the policy environment, and a fall in interest rates. This easing of borrowing conditions happens because lending by the private sector virtually disappears in overhang situations, and multilateral agencies step in with concessional rates. Thus, while debt relief is likely to improve economic policy (and especially investment) in overhang countries, it is doubtful that it would ease their terms of borrowing, or the burden of debt.
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A class of composite estimators of small area quantities that exploit spatial (distancerelated)similarity is derived. It is based on a distribution-free model for the areas, but theestimators are aimed to have optimal design-based properties. Composition is applied alsoto estimate some of the global parameters on which the small area estimators depend.It is shown that the commonly adopted assumption of random effects is not necessaryfor exploiting the similarity of the districts (borrowing strength across the districts). Themethods are applied in the estimation of the mean household sizes and the proportions ofsingle-member households in the counties (comarcas) of Catalonia. The simplest version ofthe estimators is more efficient than the established alternatives, even though the extentof spatial similarity is quite modest.
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We set up a dynamic model of firm investment in which liquidity constraintsenter explicity into the firm's maximization problem. The optimal policyrules are incorporated into a maximum likelihood procedure which estimatesthe structural parameters of the model. Investment is positively related tothe firm's internal financial position when the firm is relatively poor. This relationship disappears for wealthy firms, which can reach theirdesired level of investment. Borrowing is an increasing function of financial position for poor firms. This relationship is reversed as a firm's financial position improves, and large firms hold little debt.Liquidity constrained firms may be unused credits lines and the capacity toinvest further if they desire. However the fear that liquidity constraintswill become binding in the future induces them to invest only when internalresources increase.We estimate the structural parameters of the model and use them to quantifythe importance of liquidity constraints on firms' investment. We find thatliquidity constraints matter significantly for the investment decisions of firms. If firms can finance investment by issuing fresh equity, rather than with internal funds or debt, average capital stock is almost 35% higher overa period of 20 years. Transitory shocks to internal funds have a sustained effect on the capital stock. This effect lasts for several periods and ismore persistent for small firms than for large firms. A 10% negative shock to firm fundamentals reduces the capital stock of firms which face liquidityconstraints by almost 8% over a period as opposed to only 3.5% for firms which do not face these constraints.
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We propose a method to estimate time invariant cyclical DSGE models using the informationprovided by a variety of filters. We treat data filtered with alternative procedures as contaminated proxies of the relevant model-based quantities and estimate structural and non-structuralparameters jointly using a signal extraction approach. We employ simulated data to illustratethe properties of the procedure and compare our conclusions with those obtained when just onefilter is used. We revisit the role of money in the transmission of monetary business cycles.
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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.
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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.
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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%.
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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.
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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.