
	Where results make sense

Topic: Time series analysis

In the News (Thu 21 Aug 08)

Gordon Brown

Derby County

Mike Huckabee

Lute Olson

Pearl Harbor

Sonia Gandhi

Ricky Hatton

Narendra Modi

Jesus Christ

Rudy Giuliani

	American Time Use Survey Technical Note
		Secondary childcare time for household children is further restricted to the time between when the first household child under age 13 woke up and the last household child under age 13 went to bed.
		Time spent purchasing or talking related to purchasing meals, snacks, or beverages is not counted as part of this category; time spent doing these activities is counted in Purchas- ing goods and services.
		Time spent doing activities to care for or help any child or adult in the respondent's household, regardless of relationship to the respondent or the physical or mental health status of the person being helped, are classified here.
	www.bls.gov /news.release/atus.tn.htm (3519 words)

	IAAT (Astronomy): Time Series Analysis
		This is the homepage of the time series analysis group at the Institute for Astronomy and Astrophysics, Sect.
		One of the most fascinating time series is the sunspot number, which exhibits the well know 11y period and which additionally shows irregular behaviour on timescales from days to decades.
		At first glance, observations carried out over time periods of weeks/months suggest that the latter two phenomena are stochastic in nature, but observations over time periods of decades reveal an intriguing cyclic pattern of gradual increase and decrease in the average number of sunspots visible on the solar disk.
	astro.uni-tuebingen.de /groups/time (1144 words)

	Time Series Analysis and Forecasting Techniques (Site not responding. Last check: 2007-10-21)
		A moving average form of time series forecasting-efficient to use with seasonal patterns- easy to adjust for past errors-easy to prepare follow-on forecasts-ideal for situations where many forecasts must be prepared-several different forms are used depending on presence of trend or cyclical variations.
		It is a way to decompose a given series into stationary and nonstationary components in such a way that there sum of squares of the series from the nonstationary component is minimum with a penalty on changes to the derivatives of the nonstationary component.
		As time progresses, the accuracy of the forecasts should be closely monitored for increases in the error terms, standard error and a decrease in correlation.
	obelia.jde.aca.mmu.ac.uk /resdesgn/arsham/opre330Forecast.htm (5426 words)

	Time Series Analysis
		There are two main goals of time series analysis: (a) identifying the nature of the phenomenon represented by the sequence of observations, and (b) forecasting (predicting future values of the time series variable).
		In plots of the series, the distinguishing characteristic between these two types of seasonal components is that in the additive case, the series shows steady seasonal fluctuations, regardless of the overall level of the series; in the multiplicative case, the size of the seasonal fluctuations vary, depending on the overall level of the series.
		To contrast this technique with ARIMA or Exponential Smoothing, the purpose of spectrum analysis is to identify the seasonal fluctuations of different lengths, while in the former types of analysis, the length of the seasonal component is usually known (or guessed) a priori and then included in some theoretical model of moving averages or autocorrelations.
	www.statsoft.com /textbook/sttimser.html (13554 words)

	Time Series Analysis for Business Forecasting (Site not responding. Last check: 2007-10-21)
		Almost all time series published by the US government are already deseasonalized using the seasonal index to unmasking the underlying trends in the data, which could have been caused by the seasonality factor.
		It is the pattern generated by the time series and not necessarily the individual data values that offers to the manager who is an observer, a planner, or a controller of the system.
		It is a way to decompose a given series into stationary and non-stationary components in such a way that their sum of squares of the series from the non-stationary component is minimum with a penalty on changes to the derivatives of the non-stationary component.
	home.ubalt.edu /ntsbarsh/stat-data/Forecast.htm (10138 words)

	Macintosh Program Performs Time-Series Analysis
		Series or groups of series can be plotted on screen, with several possible options (zooming, x- and y-scaling, for example).
		The astronomical series are the eccentricity of the Earth orbit, the obliquity (the tilt) of the Earth axis, and the precessional parameter, classically defined as e sin w, where e is the eccentricity and w is (please make sure that, if possible, w is the greek letter 'omega') the longitude of the perihelion.
		Given a time series, one of the first concerns is often to identify recurrent features or periodicities, and spectral analysis is then the tool of choice.
	www.agu.org /eos_elec/96097e.html (2549 words)

	Time series analysis and forecasting, Caterpillar SSA method
		Transformation of the one-dimensional time series to the trajectory matrix by means of a delay procedure (this gives the name to the whole technique);
		Thus, the result of the 'Caterpillar'-SSA processing is a decomposition of the time series into several components, which can often be identified as trends, seasonalities and other oscillatory series, or noise components.
		The method is a powerful and useful tool of time series analysis in meteorology, hydrology, geophysics, climatology and, according to our experience, in economics, biology, physics, medicine and other sciences; that is, where short and long, one-dimensional and multidimensional, stationary and nonstationary, almost deterministic and noisy time series are to be analyzed.
	www.gistatgroup.com /cat (313 words)

	Winter School on Nonlinear Time Series Analysis (Site not responding. Last check: 2007-10-21)
		Nonlinear time series analysis is becoming a more and more reliable tool for the study of complicated dynamics from measurements.
		Despite wide interest from many disciplines, many potential users of nonlinear time series analysis are not sufficiently familiar with nonlinear methods of data analysis as to guarantee a successful application of these methods.
		Emphasis is laid on understanding the concepts of nonlinear time series analysis, on learning about algorithmic implementations, and on obtaining experience by application to data.
	www.mpipks-dresden.mpg.de /~tisean98 (302 words)

	crg@utk: Research in chaotic time-series analysis (Site not responding. Last check: 2007-10-21)
		Sampling this signal, either on a time or event basis, and recording the measured values sequentually produces a discrete signal, or time series.
		The process of analyzing time series using mathematical and numerical data transformations or even appropriate graphical displays constitutes a field of science known as time-series analysis.
		We have compiled a "Bibliography of symbolic time-series analysis" to assist in further research.
	www-chaos.engr.utk.edu /res/ctsa.html (295 words)

	Highland Statistics Ltd
		Multivariate analysis: All important multivariate techniques ((partial) canonical correspondence analysis, discriminant analysis, (partial) redundancy analysis, variance partitioning, principal component analysis, factor analysis, correspondence analysis, multidimensional scaling, clustering).
		Time series analysis: Decompose short time series in common trends, effects of explanatory variables and interactions.
		We are specialised in biological multivariate data analysis and multivariate time series data analysis.
	www.highstat.com (228 words)

	Hamilton, J.D.: Time Series Analysis.
		In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data.
		Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.
		The book is intended to provide students and researchers with a self-contained survey of time series analysis.
	pup.princeton.edu /titles/5386.html (267 words)

	Journal of Time Series Analysis - Journal Information (Site not responding. Last check: 2007-10-21)
		During the last 25 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics.
		The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications.
		The editorial board consists of many of the world's leading experts in Time Series Analysis.
	www.blackwellpublishing.com /journal.asp?ref=0143-9782 (331 words)

	Time Series Analysis and Its Applications
		Sleep data - Group 1 Categorical-valued sleep series called grp1.dat - details are in the file.
		Many time series data sets can be found here.
		These macros can be used for both time domain and frequency domain analyses.
	anson.ucdavis.edu /%7Eshumway/tsa.html (658 words)

	Citations: Recursive estimation and time-series analysis - Young (ResearchIndex)
		, andel] In addition to specific time dependent (seasonal) actuating variables for example temperature, global solar radiation, daily flow of life and so on, such signals are often subject of not or only hardly registrable actuating variables so that a prediction is combined with great.
		Further analysis revealed that the LMS rule would favor the B1 B16 representation if the experimental parameters were adjusted....
		In this paper, the model is used to estimate the phosphorus accretion rate in a sequence of divided regions along the flow path of the wetland, instead of a time series.
	citeseer.ist.psu.edu /context/15841/0 (2639 words)

	Automatic Forecasting Systems-Home,Autobox,forecasting,time series,arima,outliers,intervention,time trends
		Our heuristics are often capable of exceeding experts due to the exhaustive search based approach which considers alternative sequences to model augmentation.
		Our unique intervention detection is able to identify outliers, steps, level shifts and local time trends.
		Autobox provides a start to finish environment designed to make forecasting easy whether you have one series or one thousand.
	www.autobox.com (297 words)

	PRESS RELEASE Visual Numerics(R) Provides National Taiwan Ocean University With Advanced Numerical and Visual Data ... (Site not responding. Last check: 2007-10-21)
		With the IMSL Numerical Libraries and PV-WAVE, students and professors will be able to leverage a broad range of programming environments to develop sophisticated data analysis and visualization applications for use in maritime science and technology.
		The PV-WAVE family also includes robust time series analysis software as well as the ability to share analysis results across the enterprise with a Java-based solution.
		The IMSL Libraries are regarded as the most sophisticated, flexible, scalable and highly accessible technology available for numerical analysis in the most important mainstream programming environments in use today.
	www.marketwire.com /mw/release_html_b1?release_id=93615 (728 words)

	Time series analysis (Site not responding. Last check: 2007-10-21)
		Wavelet analysis is a generalization of Fourier analysis that allows discover of periodic behavior that only lasts a short time, or anomalous behavior for one period versus another.
		There may be other kinds of analysis you would be interested in too - perhaps based on some model of your data.
		Response #: 2 of 2 Author: asmith And there are also time-series analyses methods for predicting the future - smoothing, trend analysis of various sorts.
	www.newton.dep.anl.gov /newton/askasci/1995/math/MATH134.HTM (188 words)

	Brodgar v2
		The statistical background of most techniques in Brodgar will be published as a 700 page book by Springer-Verlag in its prestigious series 'Statistics for Biology and Health': A.F. Zuur, E.N. Ieno and G.M. Smith.
		Univariate analysis: linear regression, generalised additive modelling (GAM), semi-parametric GAM, generalised linear modelling (GLM), regression and classification trees, mixed modelling, partial linear regression, index functions, design and interaction plots.
		Time series analysis: structural time series, dynamic factor analysis, MAFA, regime shift analysis, chronological clustering, ARIMAX, spectral analysis, time lags, monthly plots, repeated Loess smoothing.
	www.brodgar.com (180 words)

	Statistics and Statistical Graphics Resources
		Rweb is a Web based interface to R (a statistical analysis package) that takes the submitted code, runs R on the code (in batch mode), and returns the output (printed and graphical).
		Time Series Data Library A collection of about 800 time series, drawn from many different fields, maintained by Rob Hyndman.
		Analysis Of Categorical Dependent Variables With SAS And SPSS.
	www.math.yorku.ca /SCS/StatResource.html (7408 words)

	SNP: A Program for Nonparametric Time Series Analysis
		Gallant, A. Ronald, and George Tauchen (1992), A Nonparametric Approach to Nonlinear Time Series Analysis: Estimation and Simulation," in David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray Rosenblatt, and Murad S. Taqqu eds.
		SNP is a method of nonparametric time series analysis.
		The method employs a Hermite polynomial series expansion to approximate theconditional density of a multivariate process.
	www.econ.duke.edu /~get/snp.html (303 words)

	time-series analysis - OneLook Dictionary Search
		We found 4 dictionaries with English definitions that include the word time-series analysis:
		Tip: Click on the first link on a line below to go directly to a page where "time-series analysis" is defined.
		Time-series analysis : Bloomberg Financial Glossary [home, info]
	www.onelook.com /?loc=rescb&w=time-series+analysis (89 words)

	Nonlinear Dynamics and Topological Time Series Analysis Archive
		This archive contains information and programs useful for nonlinear time series analysis with an emphasis on the new area of topological time series analysis and includes:
		Pointers to other nonlinear dynamics, time series analysis, and scientific software archives.
		References to some first papers in the topological analysis of chaotic time series,
	www.drchaos.net /drchaos/intro.html (453 words)

	Estima--Home of RATS Econometrics Software
		Estima develops and sells the RATS (Regression Analysis of Time Series) software package.
		RATS is a leading econometrics/time-series analysis software package used worldwide by economists and others for analyzing time series and cross sectional data, developing and estimating econometric models, forecasting, and much more.
		Also, John Frain of the Central Bank of Ireland has been kind enough to make available RATS code for implementing the Chow Lin (1971) procedure for the best linear unbiased distribution and interpolation of time series by related series.
	www.estima.com (241 words)

	Physics 505
		If you are looking for my book Chaos and Time-Series Analysis go to: http://sprott.physics.wisc.edu/chaostsa/
		Content and Level: This course is an introduction to the exciting new developments in chaos and related topics in nonlinear dynamics, including the detection and quantification of chaos in experimental data.
		You will receive one point for each assignment that you complete, and one point for handing it in on time.
	sprott.physics.wisc.edu /phys505 (358 words)

	O-Matrix: High Performance Visual Data Analysis
		5/24/2004 - Statistical Time Series Analysis Toolbox now Available
		The robust and diverse set of analysis functions enable the rapid development of complex, computationally intensive scientific, mathematical and engineering solutions.
		Since 1992, Harmonic Software has been helping scientists, engineers, and technical computing professionals in industries such as aerospace, econometrics, electrical engineering, financial modeling, and earth sciences obtain better results faster.
	www.omatrix.com (112 words)

	Neuro: Dynamic Time Series Analysis System
		Time Series Analysis System for multi-channel multi-frequency digitized analog signals
		Processes data of generic format, any digitized frequency, any number of channels.
		* Spectrum, cross-spectrum and dynamic spectrum with time lag
	www.geocities.com /somesoftware/neuro.html (81 words)

	Citations: Time-series analysis - Bradley (ResearchIndex)
		In M. Berthold and D. Hand, editors, Intelligent Data Analysis: An Introduction.
		....and domain knowledge dictate what analysis tools Pret should use to build and test models.
		Tools higher in this table are more general but their results can be less powerful.
	citeseer.ist.psu.edu /context/1496274/154099 (153 words)

	Chaos and Time-Series Analysis
		A web page supplement to the book by the above title
		It is organized according to the chapters in the book:
		FracLab Fractal Analysis Toolbox for Signal and Image Processing
	sprott.physics.wisc.edu /chaostsa (117 words)

Try your search on: Qwika (all wikis)