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- {{short description|Analysis of datasets using techniques from topology}} ...is generally challenging. TDA provides a general framework to analyze such data in a manner that is insensitive to the particular [[metric (mathematics)|me ...86 KB (12,084 words) - 09:32, 31 January 2025
- {{short description|Method of analyzing large data sets}} ...'-way array, and analysis techniques can reveal patterns in the underlying data undetected by other methods.<ref name=Coppi1989> ...7 KB (963 words) - 11:23, 26 October 2023
- ...the re-identifiability of high-dimensional [[Data anonymization|anonymous data]]. First introduced in 2013,<ref name="uinc">{{cite journal ...the number of points ''p'' needed to uniquely identify an individual in a data set. The fewer points needed, the more unique the traces are and the easier ...6 KB (797 words) - 12:57, 9 February 2025
- ...ample is a distribution. One of the main challenges in distributional data analysis is that although the space of probability distributions is a convex space, ...arycenters in the {Wasserstein} space|journal=SIAM Journal on Mathematical Analysis|volume=43|issue=2|pages=904–924|doi=10.1137/100805741|s2cid=8592977 |url=ht ...25 KB (4,044 words) - 09:44, 18 December 2024
- ...aphing]] and estimating parameters modeling the self-similarity of network data. === R/S analysis === ...11 KB (1,820 words) - 00:43, 8 August 2021
- ...ethods developed by the French school called ''Analyse des données'' (data analysis) founded by [[Jean-Paul Benzécri]]. ...ysis]] (PCA) for quantitative variables and as a [[multiple correspondence analysis]] (MCA) for qualitative variables. ...11 KB (1,621 words) - 19:44, 23 December 2023
- ...data analysis are techniques used to adjust the class distribution of a [[data set]] (i.e. the ratio between the different classes/categories represented) ...more complex oversampling techniques, including the creation of artificial data points with algorithms like [[Synthetic minority oversampling technique]].< ...20 KB (2,920 words) - 20:20, 19 February 2025
Page text matches
- ...moving average''' (ZLEMA) is a [[technical indicator]] within [[technical analysis]] that aims is to eliminate the inherent lag associated to all [[trend foll The formula for a given N-Day ''period'' and for a given ''data'' series is:<ref name="formula_chart">[http://user42.tuxfamily.org/chart/ma ...2 KB (228 words) - 02:29, 13 June 2024
- ...ries|time]] and [[Cross-sectional study|cross-sections]]). An example is a data set containing forecasts of one or multiple macroeconomic variables produce ==Analysis of multidimensional panel data== ...3 KB (434 words) - 15:50, 9 December 2016
- ...tree accumulation''' is the process of accumulating data placed in [[Tree (data structure)|tree]] nodes according to their [[Tree (data structure)|tree]] structure.<ref>{{cite thesis |type=Ph.D. |first=Jeremy |l ...2 KB (220 words) - 02:35, 16 July 2018
- ...s-covariance matrix|cross-covariance matrices]] of [[canonical correlation analysis]]. By converting <math>\operatorname{cov}(X, X)</math> and <math>\operatorn ...gested for use in the analysis of [[functional neuroimaging]] data as such data are often singular.<ref>{{Cite Q | Q129222383 }}</ref> ...2 KB (241 words) - 01:18, 20 February 2025
- {{Short description|Kinetic data structure}} ...sed as a basis for a responsive, compact and efficient kinetic minimum box data structure. ...3 KB (483 words) - 16:39, 25 April 2023
- ...ose. This method is based on the hypothesis that each item of the recorded data of a population is consistent.<ref>Searcy, J.K. and C.H. Hardison (1960). D ...ic technique|technique]] is based on the principle that when each recorded data comes from the same [[parent population]], they are consistent. ...4 KB (551 words) - 06:40, 25 September 2022
- {{Short description|Data structure}} ...ete'' and ''find-max''. They are often used as components of other kinetic data structures, such as [[kinetic closest pair]]. ...4 KB (616 words) - 19:00, 3 January 2023
- {{short description|Method of analyzing large data sets}} ...'-way array, and analysis techniques can reveal patterns in the underlying data undetected by other methods.<ref name=Coppi1989> ...7 KB (963 words) - 11:23, 26 October 2023
- {{Infobox data structure | type = [[Heap (data structure)|Heap]]/[[priority queue]] ...2 KB (317 words) - 18:49, 7 November 2024
- ...and first applied by Bross,<ref>Bross, Irwin D.J. (1958) "How to Use Ridit Analysis," ''Biometrics'', 14 (1):18-38 {{JSTOR|2527727}} ===Choosing a reference data set=== ...4 KB (568 words) - 18:34, 23 July 2023
- ...[survival analysis]], hazard rate models are widely used to model duration data in a wide range ...pdfs/STB-39-pgmhaz.pdf|title=Estimation of discrete time (grouped duration data) proportional hazards models: pgmhaz|last=Jenkins|first=Stephen P|publisher ...4 KB (536 words) - 18:45, 25 July 2024
- {{short description|Graph data structure}} ...ath> array of lists.<ref>{{Cite book|title=Statistical analysis of network data : methods and models|url=https://archive.org/details/statisticalanaly00kola ...2 KB (266 words) - 17:46, 8 January 2021
- ...ntial Moving Average''' (TEMA) is a [[technical indicator]] in [[technical analysis]] that attempts to remove the inherent lag associated with [[moving average ...he ''[[Technical Analysis of Stocks & Commodities]]'' magazine: "Smoothing Data with Faster Moving Averages"<ref name="commodities_article"/><ref name="com ...2 KB (335 words) - 23:36, 12 June 2024
- {{Short description|Smoothing of data points, digital filter}} ...e purpose of smoothing the data, that is, to increase the precision of the data without distorting the signal tendency. ...2 KB (281 words) - 16:31, 26 February 2025
- '''Hilbert spectral analysis''' is a signal analysis method applying the [[Hilbert transform]] to compute the [[instantaneous fr After performing the [[Hilbert transform]] on each signal, we can express the data in the following form: ...1 KB (186 words) - 14:00, 7 January 2025
- {{Short description|Type of data visualization}} ...rews curve for Iris data set.png|thumb|360px|An Andrews curve for the Iris data set]] ...3 KB (458 words) - 08:26, 22 January 2025
- extracted from global fits to data based on a combination of a [[Monte Carlo method]] for uncertainty estimati ...ion of a large sample of Monte Carlo replicas of the original experimental data, in a way that central values, errors and correlations are reproduced with ...5 KB (701 words) - 11:11, 27 November 2024
- ...to detect invalid pixels, and selectively smooth only invalid pixels using data coming only from valid pixels, thus avoiding to affect other features of th ...e same interval. For instance, given a pixel <math>(x,y)</math> of invalid data, its convolution kernel <math>h</math> becomes ...3 KB (396 words) - 03:02, 16 November 2020
- | title = Some mathematical notes on three-mode factor analysis ...incipal component analysis]] it may actually be generalized to higher mode analysis, which is also called [[higher-order singular value decomposition]] (HOSVD) ...5 KB (703 words) - 02:33, 17 May 2024
- ...of spatial autocorrelation that aims to account for spatial dependence of data while studying their [[covariance]].<ref>{{Cite journal ...= Multivariate spatial correlation: a method for exploratory geographical analysis ...4 KB (577 words) - 15:44, 12 September 2024