Méthodes de rééchantillonnage en méthodologie d'enquête

Le sujet principal de cette thèse porte sur l'étude de l'estimation de la variance d'une statistique basée sur des données d'enquête imputées via le bootstrap (ou la méthode de Cyrano). L'application d'une méthode bootstrap conçue pour des données d'enquête complètes (en absence de non-réponse) en présence de valeurs imputées et faire comme si celles-ci étaient de vraies observations peut conduire à une sous-estimation de la variance. Dans ce contexte, Shao et Sitter (1996) ont introduit une procédure bootstrap dans laquelle la variable étudiée et l'indicateur de réponse sont rééchantillonnés ensemble et les non-répondants bootstrap sont imputés de la même manière qu'est traité l'échantillon original. L'estimation bootstrap de la variance obtenue est valide lorsque la fraction de sondage est faible. Dans le chapitre 1, nous commençons par faire une revue des méthodes bootstrap existantes pour les données d'enquête (complètes et imputées) et les présentons dans un cadre unifié pour la première fois dans la littérature. Dans le chapitre 2, nous introduisons une nouvelle procédure bootstrap pour estimer la variance sous l'approche du modèle de non-réponse lorsque le mécanisme de non-réponse uniforme est présumé. En utilisant seulement les informations sur le taux de réponse, contrairement à Shao et Sitter (1996) qui nécessite l'indicateur de réponse individuelle, l'indicateur de réponse bootstrap est généré pour chaque échantillon bootstrap menant à un estimateur bootstrap de la variance valide même pour les fractions de sondage non-négligeables. Dans le chapitre 3, nous étudions les approches bootstrap par pseudo-population et nous considérons une classe plus générale de mécanismes de non-réponse. Nous développons deux procédures bootstrap par pseudo-population pour estimer la variance d'un estimateur imputé par rapport à l'approche du modèle de non-réponse et à celle du modèle d'imputation. Ces procédures sont également valides même pour des fractions de sondage non-négligeables.

A note on model uncertainty in linear regression

We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.

Dietary supplement use and its impact on nutritional adequacy for British Columbia and Manitoba First Nations adults living on reserve.

Contexte: L'utilisation de suppléments alimentaires est répandue chez les populations américaines et canadiennes en général, mais on en sait peu sur la consommation de suppléments alimentaires dans la population autochtone canadienne. Objectif: L'objectif général de cette étude est de prendre en compte l'utilisation de suppléments alimentaires dans l'évaluation nutritionnelle des apports alimentaires des adultes des Premières nations vivant dans les réserves en Colombie-Britannique et Manitoba. Conception: Les données ont été recueillies par l’étude ‘First Nations Food, Nutrition, and Environment Study’ de 1103 (Colombie-Britannique) et 706 (Manitoba) adultes des Premières Nations âgés de 19 à 70 ans. L'étude a utilisé un rappel alimentaire des dernières 24 heures (avec un deuxième rappel pour un sous-échantillon) pour évaluer la diète alimentaire. L'utilisation de suppléments alimentaires et des antiacides ont été recueillis par un questionnaire de fréquence. En utilisant le logiciel SIDE pour tenir compte des variations intra-individuelles dans la prise alimentaire et la technique du bootstrap pour obtenir des estimations représentatives des différentes régions, l'utilisation de suppléments de la vitamine A, D, C et de calcium ont été intégrées aux estimations de la consommation alimentaire. Résultats: Environ 30% des adultes des Premières Nations de la Colombie-Britannique et seulement 13,2% des adultes des Premières Nations du Manitoba âgés entre 19-70 ans vivant dans les réserves ont déclaré utiliser au moins un supplément alimentaire durant les 30 jours précédents. Lors de l'examen des nutriments d'intérêt, un plus faible pourcentage de la population en a fait usage, de 14,8 à 18,5% en Colombie-Britannique et de 4,9 à 8% de la population du Manitoba. La prévalence de l'usage de tout supplément alimentaire était plus élevée chez les femmes que chez les hommes dans tous les groupes d'âge et augmente avec l'âge dans les deux sexes. La plus forte prévalence d'un apport insuffisant provenant de la nourriture a été observée pour la vitamine D et le calcium en Colombie-Britannique et Manitoba, variant de 75 à 100%, et de la vitamine A dans le Manitoba (73-96%). Après avoir examiné l'utilisation de suppléments alimentaires, plus des trois quarts des participants n’ont toujours pas réussi à répondre au besoin moyen estimatif pour ces nutriments. La vitamine C est l'oligo-élément avec le plus faible pourcentage sous le besoin moyen estimatif (avec au sans suppléments) pour la Colombie-Britannique et le Manitoba. Conclusion: La majorité des adultes des Premières nations de la Colombie-Britannique et du Manitoba, même après prise en compte de l'utilisation de suppléments alimentaires, avaient des apports en vitamines A, D et des apports de calcium sous les niveaux recommandés. L'utilisation de compléments alimentaires n'a pas contribué de façon significative à l'apport total en nutriments sélectionnés sauf pour la vitamine C dans certains groupes d'âge.

Long-term Trends in Magnitude and Frequency of Extreme Rainfall Events in Florida

This study computed trends in extreme precipitation events of Florida for 1950-2010. Hourly aggregated rainfall data from 24 stations of the National Climatic Data Centre were analyzed to derive time-series of extreme rainfalls for 12 durations, ranging from 1 hour to 7 day. Non-parametric Mann-Kendall test and Theil-Sen Approach were applied to detect the significance of trends in annual maximum rainfalls, number of above threshold events and average magnitude of above threshold events for four common analysis periods. Trend Free Pre-Whitening (TFPW) approach was applied to remove the serial correlations and bootstrap resampling approach was used to detect the field significance of trends. The results for annual maximum rainfall revealed dominant increasing trends at the statistical significance level of 0.10, especially for hourly events in longer period and daily events in recent period. The number of above threshold events exhibited strong decreasing trends for hourly durations in all time periods.

Efficiency of research performance of Australian universities : a reappraisal using a bootstrap truncated regression approach

The motivation of the study stems from the results reported in the Excellence in Research for Australia (ERA) 2010 report. The report showed that only 12 universities performed research at or above international standards, of which, the Group of Eight (G8) universities filled the top eight spots. While performance of universities was based on number of research outputs, total amount of research income and other quantitative indicators, the measure of efficiency or productivity was not considered. The objectives of this paper are twofold. First, to provide a review of the research performance of 37 Australian universities using the data envelopment analysis (DEA) bootstrap approach of Simar and Wilson (2007). Second, to determine sources of productivity drivers by regressing the efficiency scores against a set of environmental variables.

Determining of the delay time for a heating ventilating and air-conditioning plant using multi-weights neurons approach

This paper presents an multi weights neurons approach to determine the delay time for a Heating ventilating and air-conditioning (HVAC) plan to respond to control actions. The multi weights neurons is a fully connected four-layer network. An acceleration technique was used to improve the general delta rule for the learning process. Experimental data for heating and cooling modes were used with both the multi weights neurons and a traditional mathematical method to determine the delay time. The results show that multi weights neurons can be used effectively determining the delay time for HVAC systems.

Technical efficiency determinants within a dual banking system:a DEA-bootstrap approach

The purpose of this study is to provide a comparative analysis of the efficiency of Islamic and conventional banks in Gulf Cooperation Council (GCC) countries. In this study, we explain inefficiencies obtained by introducing firm-specific as well as macroeconomic variables. Our findings indicate that during the eight years of study, conventional banks largely outperform Islamic banks with an average technical efficiency score of 81% compared to 95.57%. However, it is clear that since 2008, efficiency of conventional banks was in a downward trend while the efficiency of their Islamic counterparts was in an upward trend since 2009. This indicates that Islamic banks have succeeded to maintain a level of efficiency during the subprime crisis period. Finally, for the whole sample, the analysis demonstrates the strong link of macroeconomic indicators with efficiency for GCC banks. Surprisingly, we have not found any significant relationship in the case of Islamic banks.

Loan quality, ownership and efficiency of Indian banks : A bootstrap truncated regression approach

Bootstrap approaches for estimation and confidence intervals of long term memory processes

In this work, we investigate an alternative bootstrap approach based on a result of Ramsey [F.L. Ramsey, Characterization of the partial autocorrelation function, Ann. Statist. 2 (1974), pp. 1296-1301] and on the Durbin-Levinson algorithm to obtain a surrogate series from linear Gaussian processes with long range dependence. We compare this bootstrap method with other existing procedures in a wide Monte Carlo experiment by estimating, parametrically and semi-parametrically, the memory parameter d. We consider Gaussian and non-Gaussian processes to prove the robustness of the method to deviations from normality. The approach is also useful to estimate confidence intervals for the memory parameter d by improving the coverage level of the interval.

The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network

Sample complexity results from computational learning theory, when applied to neural network learning for pattern classification problems, suggest that for good generalization performance the number of training examples should grow at least linearly with the number of adjustable parameters in the network. Results in this paper show that if a large neural network is used for a pattern classification problem and the learning algorithm finds a network with small weights that has small squared error on the training patterns, then the generalization performance depends on the size of the weights rather than the number of weights. For example, consider a two-layer feedforward network of sigmoid units, in which the sum of the magnitudes of the weights associated with each unit is bounded by A and the input dimension is n. We show that the misclassification probability is no more than a certain error estimate (that is related to squared error on the training set) plus A3 √((log n)/m) (ignoring log A and log m factors), where m is the number of training patterns. This may explain the generalization performance of neural networks, particularly when the number of training examples is considerably smaller than the number of weights. It also supports heuristics (such as weight decay and early stopping) that attempt to keep the weights small during training. The proof techniques appear to be useful for the analysis of other pattern classifiers: when the input domain is a totally bounded metric space, we use the same approach to give upper bounds on misclassification probability for classifiers with decision boundaries that are far from the training examples.

Operational performance of low-cost carriers and international airlines : New evidence using a bootstrap truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil. At the same time, the European airline industry entered a period of substantive deregulation. This period witnessed opportunities for low-cost carriers to become more competitive in the market as a result of these combined events. To help assess airline performance in the aftermath of these events, this paper provides new evidence of technical efficiency for 42 national and international airlines in 2006 using the data envelopment analysis (DEA) bootstrap approach first proposed by Simar and Wilson (J Econ, 136:31-64, 2007). In the first stage, technical efficiency scores are estimated using a bootstrap DEA model. In the second stage, a truncated regression is employed to quantify the economic drivers underlying measured technical efficiency. The results highlight the key role played by non-discretionary inputs in measures of airline technical efficiency.

Efficiency and productivity of Singapore’s manufacturing sector 2001-2010: An analysis using Simar and Wilson’s (2007) bootstrapped truncated approach

This paper seeks to explain the lagging productivity in Singapore’s manufacturing noted in the statements of the Economic Strategies Committee Report 2010. Two methods are employed: the Malmquist productivity to measure total factor productivity change and Simar and Wilson’s (J Econ, 136:31–64, 2007) bootstrapped truncated regression approach. In the first stage, the nonparametric data envelopment analysis is used to measure technical efficiency. To quantify the economic drivers underlying inefficiencies, the second stage employs a bootstrapped truncated regression whereby bias-corrected efficiency estimates are regressed against explanatory variables. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Most industries were technically inefficient throughout the period except for ‘Pharmaceutical Products’. Sources of efficiency were attributed to quality of worker and flexible work arrangements while incessant use of foreign workers lowered efficiency.

Analysis of environmental efficiency variation : a materials balance approach

Recent literature has argued that environmental efficiency (EE), which is built on the materials balance (MB) principle, is more suitable than other EE measures in situations where the law of mass conversation regulates production processes. In addition, the MB-based EE method is particularly useful in analysing possible trade-offs between cost and environmental performance. Identifying determinants of MB-based EE can provide useful information to decision makers but there are very few empirical investigations into this issue. This article proposes the use of data envelopment analysis and stochastic frontier analysis techniques to analyse variation in MB-based EE. Specifically, the article develops a stochastic nutrient frontier and nutrient inefficiency model to analyse determinants of MB-based EE. The empirical study applies both techniques to investigate MB-based EE of 96 rice farms in South Korea. The size of land, fertiliser consumption intensity, cost allocative efficiency, and the share of owned land out of total land are found to be correlated with MB-based EE. The results confirm the presence of a trade-off between MB-based EE and cost allocative efficiency and this finding, favouring policy interventions to help farms simultaneously achieve cost efficiency and MP-based EE.