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Topic: Trend estimation

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	Trend - Wikipedia, the free encyclopedia
		In statistics, a trend is a long-term movement in time series data after other components have been accounted for.
		In statistics, a trend may be described in hypothesis testing, where a test has failed to achieve the benchmark for statistical significance, i.e a P-value of less than 0.05) but no more than 0.01.
		In behavioral finance, a trend is interpreted as a three-step market price upward or downward move due to the reactions of investors as a social group to known information: 1/ underreaction, 2/ adjustment, 3/ overreaction.
	en.wikipedia.org /wiki/Trend (269 words)

	Read about Trend at WorldVillage Encyclopedia. Research Trend and learn about Trend here! (Site not responding. Last check: 2007-09-07)
		trend is a long-term movement in time series data after other components have been accounted for.
		trend is the existing general direction of energy expressed as the relationship between prices.
		trend is interpreted as a three-step market price upward or downward move due to the reactions of investors as a social group to known information: 1/ underreaction, 2/ adjustment, 3/ overreaction.
	encyclopedia.worldvillage.com /s/b/Trend (196 words)

	Trend estimation - Wikipedia, the free encyclopedia
		When a series of measurements of a process is treated as a time series, trend estimation is the application of statistical techniques to make and justify statements about trends in the data.
		Assuming the underlying process is a physical system that is incompletely understood, one may thereby construct a model, independent of anything known about the physics of the process, to explain the behaviour of the measurement.
		If we consider a concrete example, the global surface temperature record of the past 140 years as presented by the IPCC: [2], then the interannual variation is about 0.2°C and the trend about 0.6°C over 140 years, with 95% confidence limits of 0.2°C (by coincidence, about the same value as the interannual variation).
	www.wikipedia.org /wiki/Trend_estimation (1222 words)

	Details: Trend Estimation
		In this analysis, trend (or a consistent change in counts of birds on a route) is the quantity that is estimated, and annual indices of abundance are used to assess higher levels of pattern in the data in the context of the trend.
		Regional trends are estimated as a weighted average of trends on individual routes.
		Route trends are estimated using the estimating equations estimator described by Link and Sauer (1994), in which a multiplicative trend is estimated.
	www.mbr-pwrc.usgs.gov /bbs/grass/trendin.htm (653 words)

	Trend estimation - Wikipedia, the free encyclopedia
		Before we can consider trends in real data, we need to understand trends in random data.
		Then we may say that, at degree of certainty S, any trend in the data cannot be distinguished from random noise.
		From the above discussion of trends in random data with known variance, we know the distribution of trends to be expected from random (trendless) data.
	en.wikipedia.org /wiki/Trend_estimation (1222 words)

	AusStats : 1998 Feature Article - Improvements to Trend Estimation for National Accounts Aggregates
		Presently, ABS practice is to derive the trend estimates of national accounts aggregates by summing the trend estimates of their components.
		Trend estimates are calculated by smoothing the seasonally adjusted series using a statistical procedure based on centred Henderson moving averages.
		Overall, revision to the trend estimates of aggregates should be reduced, however there may be a greater revision to the estimates whenever there are large irregular movements in the seasonally adjusted estimate of the aggregate.
	abs.gov.au /AUSSTATS/abs@.nsf/Lookup/758E274004917D5CCA256FCE0011818C (1086 words)

	Using Trend Variables
		This trend variable can serve as a proxy for a variable that affects the dependent variable and is not directly observable -- but is highly correlated with time.
		For the estimation of consumption functions a trend variable may serve as a proxy for changes in consumer preferences.
		The estimation results show that the estimated coefficient for the time trend variable is negative and statistically significant.
	shazam.econ.ubc.ca /intro/trend.htm (993 words)

	Trend estimation (Site not responding. Last check: 2007-09-07)
		A series of measurements of a process may be treated as a time series, and then trend estimation is the application ofstatistical techniques to make and justify statements about trends in the data.
		Assuming the underlying process is a physicalsystem that is incompletely understood, one may thereby construct a model, independent of anything known about the physics of theprocess, to explain the behaviour of the measurement.
		From the abovediscussion of trends in random data with known variance, we know the distribution of trends to be expected from random(trendless) data.
	www.therfcc.org /trend-estimation-218113.html (1049 words)

	Cancer Control and Population Sciences: Current Research
		These models address the problem of estimation and bias in log-linear regression models with exact collinearity between the effects of age, period and cohort in APC analysis.
		A unique estimator is identified, which generates accurate trend estimation with minimal bias or no bias.
		The ultimate goal of the investigation is to assess trend estimation and forecasting in APC analyses.
	dccps.nci.nih.gov /grants/abstract.asp?applid=6377465 (336 words)

	wavelets2
		We use non-decimated wavelet approximations to estimate trends at coarse scales (e.g.
		The decimated wavelet approximations are sensitive to the shape of the basis wavelets used, and this is particularly evident at coarse scales.
		At finer scales, the difference between trend estimates from using decimated versus non-decimated wavelet transforms is marginal, and since decimated wavelets conserve energy and are much more efficient to compute, we use them for short-term trend estimation.
	www.stats.ox.ac.uk /~sen/wavelets2.html (415 words)

	Details: Trend Estimation (Site not responding. Last check: 2007-09-07)
		In this analysis, trend (or a consistent change in counts of birds on a circle) is the quantity that is estimated, and annual indices of abundance are used to assess higher levels of pattern in the data in the context of the trend.
		Regional trends are estimated as a weighted average of trends on individual circles.
		Circle trends are estimated from linear regression of the natural logarithm of effort-adjusted counts (plus 0.5 to accommodate 0 counts) on year of survey.
	www.mbr-pwrc.usgs.gov /bbs/trecbcin.html (507 words)

	AusStats : Appendix 3 - Seasonally adjusted and trend estimates
		The estimated seasonal and calendar influences, together with certain prior adjustment factors, provide the combined adjustment factors by which the original series is seasonally adjusted.
		It is particularly difficult to identify and estimate the trend and seasonal components at times of rapid or abrupt changes in these components.
		While the asymmetric weights enable trend estimates for recent periods to be produced, they result in revisions to the estimates when subsequent observations are available.
	www.abs.gov.au /ausstats/ABS@.nsf/66f306f503e529a5ca25697e0017661f/313778ba8bd656fcca2569a40006165c!OpenDocument (1645 words)

	mistype.info: trend trading variant information page (Site not responding. Last check: 2007-09-07)
		Therefore whenever a stock goes against the general trend you are justified in assuming that there is something wrong with that particular stock.
		The trend has been established before the news is published, and in bull markets bear items are ignored and bull news exaggerated, and vice versa.
		This trend trading variant index site has been developed to help wayward users find the information they are looking for, no matter how they are mistakenly spelled or mistyped.
	www.mistype.info /trend%20trading.htm (271 words)

	Peter Craigmile's Colloquium (Site not responding. Last check: 2007-09-07)
		A common problem in the analysis of environmental time series is how to deal with a possible trend component, which is usually thought of as large scale (or low frequency) variations or patterns in the series that might be best modelled separately from the rest of the series.
		Trend is often confounded with low frequency stochastic fluctuations, particularly in the case of models such as fractionally differenced (FD) processes, which can account for long memory dependence (slowly decaying auto-correlation) and can be extended to encompass non-stationary processes exhibiting quite significant low frequency components.
		The estimation of the process parameters is based on an approximative maximum likelihood approach that is made possible by the fact that the DWT decorrelates FD process approximately.
	www.stat.ohio-state.edu /~seminar/2001/STATS/craigmile.html (203 words)

	Trend estimation (Site not responding. Last check: 2007-09-07)
		, any trend in the data cannot be distinguished from random noise.
		the trend will be buried in the noise.
		If we consider a concrete example, the global surface temperature record of the past 140 years as presented by the IPCC: [1], then the interannual variation is about 0.2°C and the trend about 0.6°C over 140 years, with 95% confidence limits of 0.2°C (by coincidence, about the same value as the interannual variation).
	www.sciencedaily.com /encyclopedia/trend_estimation (1101 words)

	Projects (Site not responding. Last check: 2007-09-07)
		Trend is often confounded with low frequency stochastic fluctuations, particularly in the case of models such as fractionally differenced processes (FDPs), which can account for long memory dependence (slowly decaying auto-correlation) and can be extended to encompass non-stationary processes exhibiting quite significant low frequency components.
		We assume a model of polynomial trend plus fractionally differenced noise and apply the discrete wavelet transform (DWT) to separate a time series into pieces that can be used to estimate both the FDP parameters and the trend.
		The estimation of the FDP parameters is based on an approximation maximum likelihood approach that is made possible by the fact that the DWT decorrelates FDPs approximately.
	www.nrcse.washington.edu /research/st-16.html (193 words)

	Bayesian Estimation of Genetic Trend F. Jay Breidt and Alicia L. Carriquiry Department of Statistics, Iowa State ... (Site not responding. Last check: 2007-09-07)
		Given phenotypic records for animals born in different time periods (denoted here by generations), a mixed effects model is fitted to all the observations and predictors for the random effects in the model are computed.
		Then, the means for the random effect corresponding to each generation are obtained, and these generation means are then used to fit a model for trend estimation and forecasting.
		Bayesian computations are not straightforward, since the timedependent mixed model imposes a constraint on the value of the components of variance in the model.
	web.uct.ac.za /depts/maths/isba96/abstracts/node8.html (290 words)

	Information Bridge: DOE Scientific and Technical Information (Site not responding. Last check: 2007-09-07)
		Random variation in data may obscure real trends or may produce the illusion of a trend where none exists, so statistical methods are needed to reliably detect and estimate trends.
		Trend detection uses statistical hypothesis testing and provides a yes or no answer regarding the existence of a trend.
		To quantify the magnitude of a trend, estimation is required.
	www.osti.gov /bridge/product.biblio.jsp?osti_id=34368 (351 words)

	One may choose to dedicate half of the observations to the purposes of each estimating trend and covariogram (i (Site not responding. Last check: 2007-09-07)
		One may choose to dedicate half of the observations to the purposes of each estimating trend and covariogram (i
		One may choose to dedicate half of the observations to the purposes of each estimating trend and covariogram (i.e.
		The result is displayed below and it clearly combines the virtues of the two approaches, the region is both covered regularly and a cluster to generate short lags is also included.
	statistik.wu-wien.ac.at /stat4/mueller/csd/6-3.htm (86 words)

	PCMDI Report 55 (Site not responding. Last check: 2007-09-07)
		This paper examines trend uncertainties in layer-average free atmosphere temperatures arising from the use of different trend estimation methods.
		Trend fitting by the LA method can degrade the lower-tropospheric trend agreenebt of 0.03ºC/decade (over 1979-1996) previously reported for the MSU and radiosonde data.
		To examine trend differences between data sets we compute 95% confidence intervals for individual trends and show that these overlap fir almost all data sets considered.
	www-pcmdi.llnl.gov /publications/ab59.html (358 words)

	Trend Analysis Methods on Almondnet (Site not responding. Last check: 2007-09-07)
		Trend Analysis: Uses linear and nonlinear regression with time as the explanatory variable-used where...
		practice of analysing trend line breaks, there are dozens of methods used in the technical analysis of stock and...
		Trend forecasting is one of the most effective methods of fashion forecasting...
	www.ncpm.co.uk /popmusic/trend_analysis_methods.html (375 words)

	Trend estimation - Enpsychlopedia (Site not responding. Last check: 2007-09-07)
		Such a distribution will be normal (Central limit theorem except in pathological cases, since (in a slightly non-obvious way of thinking about it) the trend is a linear combination of the $y_i$ ) and (if the series genuinely is random) centered on zero.
		It is simplest if the $e$ 's all have the same distribution, but if not (if some have higher variance, meaning that those data points are effectively less certain) then this can be taken into account during the least squares fitting, by weighting each point by the inverse of the variance of that point.
		If the calculated trend, $a$ , is larger than the value, $V$ , then the trend is deemed significantly different from zero at significance level $S$ .
	www.grohol.com /psypsych/Trend_estimation (1242 words)

	[No title] (Site not responding. Last check: 2007-09-07)
		The identification of a trend is a nontrivial problem and I emphasize that there exists no trend estimation procedure for spatial processes with unknown dependence structure.
		Exploratory tools for the empirical variogram or for the observed process, as well as a commonly used parametric and nonparametric method for trend estimation are illustrated.
		A simple method that evolved out of the consequences of visual data analysis is developed, namely variogram estimation based on `local trend estimation'.
	amath.colorado.edu /seminars/2002fall/Abstracts/furrer.html (161 words)

	Henderson trend filter \| Henderson Moving Average
		The Australian Bureau of Statistics uses the Henderson moving averages to calculate trend estimates.
		For some general information about trend estimates and interpreting movements in a time series check out a talk on A Guide to Interpreting Time Series.
		Trend estimates should only be calculated on seasonally adjusted estimates.
	www.uow.edu.au /~craigmc/henderson.html (972 words)

	StatLab Abstracts by Author
		Abstract: REACT estimators for the mean of a linear model involve three steps: transforming themodel to a canonical form that provides an economical representation of the unknown meanvector, estimating the risks of a class of candidate linear shrinkage estimators, and adaptivelyselecting the candidate estimator that minimizes estimated risk.
		Furthermore, theasymptotic bias of the univariate Burg estimator to terms of 1/n is shown to be thesame as the bias of the least-squares estimator; n is the number ofobservations.
		A pitch estimator based on this theory is investigated with respect tothe shift of the pitch of the residue described by Schouten et al.(Schouten, J.F.,Ritsma, R.J., Lopes Cardozo: Pitch of the residue, J.
	www.statlab.uni-heidelberg.de /reports/AbstractsByAuthor.html (9183 words)

	Matlab Captain Toolbox for time series analysis and forecasting
		Fixed Interval Smoothing (FIS) estimates of the TVPs are obtained, under the assumption that the parameters vary as one of the family of generalised random walks: Random Walk (RW); Integrated Random Walk (IRW); Smoothed Random Walk (SRW); Local Linear Trend (LLT); and 1st order autoregression (AR(1)).
		It provides smoothed estimates of the series, as well as all its components (trend, fundamental frequency and harmonic components), together with the estimated changing amplitude and phase of the latter.
		Here, the trend is extracted from the time series and a peturbational component about the trend is modelled as a pure AR component.
	www.es.lancs.ac.uk /cres/captain/tvp.html. (744 words)

	Trend-oriented sampling strategy and estimation of soluble reactive phosphorus loads in streams
		Consequently, stream-based estimation of long-term changes in nutrient leaching is masked by variations of stream discharge.
		Monte Carlo simulations are carried out to determine monitoring strategies for optimizing the number of water samples, their distribution between periods of low and high discharge, and the duration of composite sample collection.
		Trends in SRP load are isolated from natural variations by applying the discharge time series of 1 year each to annually changing rating curves.
	www.agu.org /pubs/crossref/2005/2004WR003539.shtml (326 words)

	Statistical Significance of Trends and Trend Differences in Layer-Average Atmospheric Temperature Time Series (Site not responding. Last check: 2007-09-07)
		Trend analyses and comparisons are given over a range of time intervals.
		Trend fitting by minimization of absolute deviations degrades the previously reported global lower tropospheric trend agreement of 0.03°C/decade between the MSU and radiosonde data.
		Significant trends in d(t) are also found between different versions of the MSU channel 4 data, and between channel 4 time series bases on globally-complete MSU data and on MSU data subsampled with the incomplete rediosonde coverage.
	www.cgd.ucar.edu /cas/abstracts/files/Wigley2000_5.html (393 words)

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