Relevant bibliographies by topics / Mean square errors / Books
To see the other types of publications on this topic, follow the link: Mean square errors.

Books on the topic 'Mean square errors'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 21 books for your research on the topic 'Mean square errors.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse books on a wide variety of disciplines and organise your bibliography correctly.

1

Gaver, Donald Paul. Bayesian prediction of mean square errors with covariates. Monterey, Calif: Naval Postgraduate School, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Patterson, K. D. Revisions to the national income accounts: A multiplicative decomposition of mean square errors. Reading: University of Reading. Department of Economics, 1990.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Clements, Michael P. On the limitations of comparing mean square forecast error. Oxford: Oxford University, Institute of Economics and Statistics, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Baram, Yoram. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Hoque, Asraul. The exact multiperiod mean-square forecast error for the first-order autoregressive model. London: London School of Economics, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Clark, Todd E. Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis. Kansas City [Mo.]: Research Division, Federal Reserve Bank of Kansas City, 2004.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Magnus, Jan R. The exact multiperiod mean-square forecast error for the first-order autoregressive modelwith an intercept. London: National Institute of Economic and Social Research, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Magnus, Jan R. The exact multiperiod mean-square forecast error for the first-order autoregressive model with an intercept. London: International Centre for Economics and Related Disciplines, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., ed. Measured and predicted root-mean-square errors in square and triangular antenna mesh facets. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., ed. Measured and predicted root-mean-square errors in square and triangular antenna mesh facets. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
11

National Aeronautics and Space Administration (NASA) Staff. Measured and Predicted Root-Mean-Square Errors in Square and Triangular Antenna Mesh Facets. Independently Published, 2019.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
12

United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., ed. A root-mean-square pressure fluctuations model for internal flow applications. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
13

A root-mean-square pressure fluctuations model for internal flow applications. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
14

Cardot, Hervé, and Pascal Sarda. Functional Linear Regression. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.2.

Full text
Abstract:
This article presents a selected bibliography on functional linear regression (FLR) and highlights the key contributions from both applied and theoretical points of view. It first defines FLR in the case of a scalar response and shows how its modelization can also be extended to the case of a functional response. It then considers two kinds of estimation procedures for this slope parameter: projection-based estimators in which regularization is performed through dimension reduction, such as functional principal component regression, and penalized least squares estimators that take into account a penalized least squares minimization problem. The article proceeds by discussing the main asymptotic properties separating results on mean square prediction error and results on L2 estimation error. It also describes some related models, including generalized functional linear models and FLR on quantiles, and concludes with a complementary bibliography and some open problems.
APA, Harvard, Vancouver, ISO, and other styles
15

G, Kalit, and Ames Research Center, eds. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
16

G, Kalit, and Ames Research Center, eds. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
17

Siripanich, Pachitjanut Dasnanjali. Estimating root mean squared error in the one-way random model. 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
18

O'Donnell, Eileen M. A mean squared error of prediction approach to the analysis of the combined array. 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
19

Cortes-Colon, William. An analysis of the BOOTSTRAP method for estimating the mean squared error of statistical estimators. 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
20

Walsh, Bruce, and Michael Lynch. Analysis of Short-term Selection Experiments: 1. Least-squares Approaches. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0018.

Full text
Abstract:
This chapter examines short-term (a few generations) selection response in the mean of a trait. Traditionally, such experiments are analyzed using least-squares (LS) approaches. While ordinary LS (OLS) is often used, genetic drift causes the residual to be both correlated and heteroscedastic, resulting in the sampling variances given by OLS being too small. This chapter details the appropriate general LS (GLS) approaches to properly account for this residual error structure. It also reviews some of the common features observed in short-term selection experiments and examines experimental designs, such as the use of a control population versus a divergence-selection approach. It concludes by discussing another linear model used mainly by plant breeders, generation-means analysis (GMA), wherein remnant seed for several generations of response are crossed and then grown in a common garden. Such an analysis can provide insight into the genetic nature of any response.
APA, Harvard, Vancouver, ISO, and other styles
21

Furst, Eric M., and Todd M. Squires. Multiple particle tracking. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199655205.003.0004.

Full text
Abstract:
The fundamentals and best practices of multiple particle tracking microrheology are discussed, including methods for producing video microscopy data, analyzing data to obtain mean-squared displacements and displacement correlations, and, critically, the accuracy and errors (static and dynamic) associated with particle tracking. Applications presented include two-point microrheology, methods for characterizing heterogeneous material rheology, and shell models of local (non-continuum) heterogeneity. Particle tracking has a long history. The earliest descriptions of Brownian motion relied on precise observations, and later quantitative measurements, using light microscopy.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the bibliographies on the topic 'Mean square errors' for other source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography