A Method for Computing the Incomplete Beta Function Ratio. Revised

DiDonato, A. R.; Jarnagin, M. P.

doi:10.21236/ad0642495

Cited by 5 publications

(10 citation statements)

References 2 publications

(3 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…JNOTE. In "orthogonal" analysis of variance one would write the model, for this case of all factors being quantitative, in the conventional way (2-3) rather than in the way of (2)(3)(4)(5)(6)(7).…”

Section: O2mentioning

confidence: 99%

“…The prediction power for y of this set may be tested by F. of (2)(3)(4)(5)(6)(7)(8)(9)(10), that is, the null hypothesis that the set of N-N' No. do not have azW predi1ction power for y may be tested.…”

Section: O ' 'mentioning

confidence: 99%

“…The non-significance is the tail area under the density curve of F to the right of the calculated vrAlue F. . One can easily see from (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12) that the non-significance equals, the significance level ot in the teat (2-10) when %* equals F,_...…”

Section: O ' 'mentioning

confidence: 99%

“…These pooling procedures (marked by one, two, or three " +"-signs attached to the step number of the ranking) increase the error sum of squares, thereby decreasing the F-v.lue of (2-10) and increasing the I(X)-value according to (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12).…”

Section: 'mentioning

confidence: 99%

“…This column gives the F-value of the Main Theorem, see (2)(3)(4)(5)(6)(7)(8)(9)(10) in Section 2.1.2, as computed for the CIV or effect ranked at the given step, for the cumulative or the single dropping procedure, as applicable.…”

Section: S "Diff Ms"mentioning

confidence: 99%

See 4 more Smart Citations

The Method and Use of Novacom, a Program for 'Non-Orthogonal' Analysis of Variance and Covariance

K¹

1968

View full text Add to dashboard Cite

The report contains the description of a program ("NOVACCI") for the solution of problems in the area of analyzing "data based on the general linear statistical model. While the detailed program documentation is riven elsewhere, the present publication deals with the statistical method, the logical flow, and the use and application of NOJACC4 in multiple linear regression and (" non-orthogonal") analysis of variance and. covariance for crossed classifications with incomplete and unbalanced data. The method of NOVACC14 is basically a backward ranking procedure applied to individual and/or groups of independent variables (concomitant independent variables and/or AINOVA effects, respectively). The result o-L the ranking is a model ("significant model") which contains only significant concomitant independent variables and/or AflOVA effects. The method and use of the program is illustrated by examples of the statistical analysis of bodies of incomplete experimental data.

show abstract

Section: O2mentioning

confidence: 99%

Section: O ' 'mentioning

confidence: 99%

Section: O ' 'mentioning

confidence: 99%

Section: 'mentioning

confidence: 99%

Section: S "Diff Ms"mentioning

confidence: 99%

See 3 more Smart Citations

The Method and Use of Novacom, a Program for 'Non-Orthogonal' Analysis of Variance and Covariance

K¹

1968

View full text Add to dashboard Cite

show abstract

The efficient calculation of the incomplete beta-function ratio for half-integer values of the parameters 𝑎,𝑏

DiDonato¹,

Jarnagin²

1967

Math. Comp.

Self Cite

View full text Add to dashboard Cite

Memory Vectors for Similarity Search in High-Dimensional Spaces

İşcen

Furon

Gripon

et al. 2018

IEEE Trans. Big Data

View full text Add to dashboard Cite

We study an indexing architecture to store and search in a database of high-dimensional vectors from the perspective of statistical signal processing and decision theory. This architecture is composed of several memory units, each of which summarizes a fraction of the database by a single representative vector. The potential similarity of the query to one of the vectors stored in the memory unit is gauged by a simple correlation with the memory unit's representative vector. This representative optimizes the test of the following hypothesis: the query is independent from any vector in the memory unit vs. the query is a simple perturbation of one of the stored vectors. Compared to exhaustive search, our approach finds the most similar database vectors significantly faster without a noticeable reduction in search quality. Interestingly, the reduction of complexity is provably better in high-dimensional spaces. We empirically demonstrate its practical interest in a large-scale image search scenario with off-the-shelf state-of-the-art descriptors. Index Terms-High-dimensional indexing, image indexing, image retrieval. ! • A. Iscen and T. Furon are with Inria.

show abstract

A Method for Computing the Incomplete Beta Function Ratio. Revised

Cited by 5 publications

References 2 publications

The Method and Use of Novacom, a Program for 'Non-Orthogonal' Analysis of Variance and Covariance

The Method and Use of Novacom, a Program for 'Non-Orthogonal' Analysis of Variance and Covariance

The efficient calculation of the incomplete beta-function ratio for half-integer values of the parameters 𝑎,𝑏

Memory Vectors for Similarity Search in High-Dimensional Spaces

Contact Info

Product

Resources

About