Search Results - subject:"missing values"

A Semiparametric Approach for Analyzing Nonignorable Missing Data

Xie, Hui - 2010

In missing data analysis, there is often a need to assess the sensitivity of key inferences to departures from untestable assumptions regarding the missing data process. Such sensitivity analysis often requires specifying a missing data model which commonly assumes parametric functional forms...

Persistent link: https://www.econbiz.de/10012462387

Generalized canonical correlation analysis with missing values

van de Velden, van de Velden, M.; Takane, Y. - Faculteit der Economische Wetenschappen, Erasmus … - 2009

Two new methods for dealing with missing values in generalized canonical correlation analysis are introduced. The first … analysis. In the second approach, missing values are imputed in such a way that the generalized canonical correlation analysis …

Persistent link: https://www.econbiz.de/10011149292

Generalized canonical correlation analysis with missing values

Velden, M. van de; Takane, Y. - Erasmus University Rotterdam, Econometric Institute - 2009

Persistent link: https://www.econbiz.de/10008570623

Compensating for missing data in the SOEP

Spieß, Martin - 2009

Persistent link: https://www.econbiz.de/10008840053

Calibrated imputation of numerical data under linear edit restrictions

Pannekoek, Jeroen; Shlomo, Natalie; Waal, Ton de - 2009

missing data in data sets is imputation, where missing values are estimated and filled in. An important problem of … M i=r x r1 x r2 x r3 Total X 1 X 2 X 3 These columns contain missing values that require imputation. Just as the … missing values with imputations, such that the sum constraint (8) and the interval constraints (9) are satisfied. Below we …

Persistent link: https://www.econbiz.de/10003863409

Estimating with kernel smoothers the mean of functional data in a finite population setting. A note on variance estimation in presence of partially observed trajectories

Cardot, Hervé; De Moliner, Anne; Goga, Camelia - In: Statistics & Probability Letters 99 (2015) C, pp. 156-166

kernel estimators for the mean curve in presence of discretized trajectories with missing values. Their pointwise variances …

Persistent link: https://www.econbiz.de/10011208308

A novel approach for imputation of missing continuous attribute values in databases using genetic algorithm

Devi Priya, R.; Kuppuswami, S. - In: International journal of information technology and … 14 (2015) 2/3, pp. 185-200

Persistent link: https://www.econbiz.de/10011526987

Weighting and imputation for missing data in a cost and earnings fishery survey

Lew, Daniel K.; Himes-Cornell, Amber; Lee, Jean - In: Marine resource economics 30 (2015) 2, pp. 219-230

Persistent link: https://www.econbiz.de/10011313743

Mata Matters: Overflow, underflow and the IEEE floating-point format

Linhart, Jean Marie - In: Stata Journal 8 (2008) 2, pp. 255-268

Mata is Stata’s matrix language. The Mata Matters column shows how Mata can be used interactively to solve problems and as a programming language to add new features to Stata. In this quarter’s column, we investigate underflow and overflow and then delve into the details of how...

Persistent link: https://www.econbiz.de/10005748357

Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP

Marcellino, Massimiliano; Schumacher, Christian - Department of Economics, European University Institute - 2008

This paper compares different ways to estimate the current state of the economy using factor models that can handle unbalanced datasets. Due to the different release lags of business cycle indicators, data unbalancedness often emerges at the end of multivariate samples, which is sometimes...

Persistent link: https://www.econbiz.de/10005557690