نتایج جستجو برای: Wahba Zuḥaylī

تعداد نتایج: 110  

Khadīja Aḥmadī Bīghash ‘Alī Aswadī

The science of interpretation has a special position in the Islamic sciences and has been addressed seriously by Muslims from the very first days of Islam, because interpretation is to understand and discover the points of the best speech, i.e. the speech of the Sublime Allāh. One of the new commentaries on Muslims' divine book is al-Tafsīr al-munīr fī al-‘aqīda wa al-sharī‘a wa al-munhaj, auth...

Journal: :Statistical Science 2020

2012
Renato Zanetti Thomas Ainscough John Christian Pol D. Spanos

The well-known Wahba Problem [1] is a non-linear, weighted least-squares problem that seeks to obtain the optimal attitude matrix from a set of at least two independent vector measurements. The most common technique used to solved the Wahba problem is the so-called q-method, developed by Davenport and documented in [2]. The q-method rearranges the Wahba performance index into a quadratic perfor...

2005
Kurt S. Riedel Kaya Imre

We adapt the interactive spline model of Wahba to growth curves with covariates. The smoothing spline formulation permits a nonparametric representation of the growth curves. In the limit when the discretization error is small relative to the estimation error, the resulting growth curve estimates often depend only weakly on the number and locations of the knots. The smoothness parameter is dete...

2002
ANNA LIU YUEDONG WANG

Nonparametric regression models are often used to check or suggest a parametric model. Several methods have been proposed to test the hypothesis of a parametric regression function against an alternative smoothing spline model. Some tests such as the locally most powerful (LMP) test by Cox et al. (Cox, D., Koh, E., Wahba, G. and Yandell, B. (1988). Testing the (parametric) null model hypothesis...

2002
Simon N. Wood Nicole H. Augustin

Generalized Additive Models (GAMs) have been popularized by the work of Hastie and Tibshirani (1990) and the availability of user friendly GAM software in Splus. However, whilst it is flexible and efficient, the GAM framework based on backfitting with linear smoothers presents some difficulties when it comes to model selection and inference. On the other hand, the mathematically elegant work of...

2000
Jeffrey A. Smit Petra Todd Jeffrey Smith

This paper applies recently developed cross-sectional and longitudinal propensity score matching estimators to data from the National Supported Work Demonstration that have been previously analyzed by LaLonde (1986) and Dehejia and Wahba (1998,1999). We find little support for recent claims in the econometrics and statistics literatures that traditional, cross-sectional matching estimators gene...

Journal: :Journal of statistical planning and inference 2010
Grace Wahba

We summarize, review and comment upon three papers which discuss the use of discrete, noisy, incomplete, scattered pairwise dissimilarity data in statistical model building. Convex cone optimization codes are used to embed the objects into a Euclidean space which respects the dissimilarity information while controlling the dimension of the space. A "newbie" algorithm is provided for embedding n...

2008
Douglas Nychka

A smoothing spline estimator can be interpreted in two ways: either as the solution of a variational problem or as the posterior mean when a particular Gaussian prior is placed on the unknown regression function. In order to explain the remarkable performance of her Bayesian "confidence intervals" in a simulation study, Wahba (1983) conjectured that the mean posterior variance of a spline estim...

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  • "; pgn_html+=pgn_li; } document.getElementById("pgn-ul").innerHTML=pgn_html var pgn_links = document.querySelectorAll('.mypgn'); pgn_links.forEach(function(pgn_link) { pgn_link.addEventListener('click', paginate) }) } function post_and_fetch(data,url) { showLoading() xhr = new XMLHttpRequest(); xhr.open('POST', url, true); xhr.setRequestHeader('Content-Type', 'application/json; charset=UTF-8'); xhr.onreadystatechange = function() { if (xhr.readyState === 4 && xhr.status === 200) { var resp = xhr.responseText; resp_json=JSON.parse(resp) resp_place = document.getElementById("search_result_div") resp_place.innerHTML = resp_json['results'] search_meta = resp_json['meta'] update_search_meta(search_meta) update_pagination() hideLoading() } }; xhr.send(JSON.stringify(data)); } function unfilter() { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":"unfilter", "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } function deactivate_all_bars(){ var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(bar) { bar.dataset.active = false bar.style = "stroke:#71a3c5;" }) } year_chart.on("created", function() { var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(check) { check.addEventListener('click', checkIndex); }) }); function checkIndex(event) { var yrchart = document.querySelectorAll('.ct-bar'); var year_bar = event.target if (year_bar.dataset.active == "true") { unfilter_res = unfilter() year_bar.dataset.active = false year_bar.style = "stroke:#1d2b3699;" } else { deactivate_all_bars() year_bar.dataset.active = true year_bar.style = "stroke:#e56f6f;" filter_year = chart_data['labels'][Array.from(yrchart).indexOf(year_bar)] url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":filter_year, "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } } function showLoading() { document.getElementById("loading").style.display = "block"; setTimeout(hideLoading, 10000); // 10 seconds } function hideLoading() { document.getElementById("loading").style.display = "none"; } -->