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	Semivariance (Site not responding. Last check: 2007-11-07)
		The semivariance is simply half the variance of the differences between all possible points spaced a constant distance apart.
		The semivariogram is a plot of semivariance as a function of distance between the observations, and is the source of information used in kriging to achieve optimal weighting functions for mapping.
		Kriging uses the semivariogram, or rather a mathematical model of the semivariogram, in calculating estimates of the surface at the grid nodes.
	www.kgs.ku.edu /Tis/surf3/s3krig2.html (266 words)

	Submeter Spatial Variability of Selected Soil and Plant Variables (Site not responding. Last check: 2007-11-07)
		Semivariance analysis was used to estimate the range over which samples of the five soil variables (total N, extractable P, and K, organic C, and pH) and two plant variables (N concentration and biomass) were related.
		Semivariance analysis is a geostatistical analysis method used to estimate the distance or range over which samples of a regionalized variable have related variances (Royle et al., 1980).
		Semivariances are customarily plotted as a function of h and are termed semivariograms.
	www.nue.okstate.edu /Papers/Microvariability_Solie_GeoStat.htm (5302 words)

	FPA Journal - Semivariance in Asset Allocations: Longer Horizons Can Handle Riskier Holdings
		This article uses semivariance and standard deviation as risk measures in determining the historically optimal allocations to a bond index or a small-stock index with a large-stock index over investment horizons of 5, 10, 15, and 20 years.
		The standard deviations and semivariances generally increase for the corporate bonds and decrease for the stocks, the longer the investment horizon.
		This support is consistent whether the risk measure of interest is standard deviation or semivariance, with optimal portfolio allocation suggestions based on the Sharpe ratio and the reward-to-semivariability ratio.
	www.fpanet.org /journal/articles/2007_Issues/jfp0107-art7.cfm (3783 words)

	geekdom (Site not responding. Last check: 2007-11-07)
		The semivariance is based on the idea that two points close together are likely to be more similar to each other than two points farther apart.
		So in other words the semivariance for all points that are separated by a given distance, you are calculating half the average variance between each pair of points (hence 'semi' variance).
		The value of the semivariance at the range is called the 'sill' and the sill minus the nugget is the 'partial sill'.
	www.tracyhicks.com /geek.htm (657 words)

	KRIGING
		Semivariance is a measure of the degree of spatial dependence between samples.
		The plot of the semivariances as a function of distance from a point is referred to as a semivariogram.
		The semivariance increases as the distance increases until at a certain distance away from a point the semivariance will equal the variance around the average value, and will therefore no longer increase, causing a flat region to occur on the semivariogram called a sill.
	ewr.cee.vt.edu /environmental/teach/smprimer/kriging/kriging.html (1687 words)

	Statistics and Phylogenetic Community Ecology — Truman's Mathematical Biology Initiative
		Semivariance is more appropriate if the purpose of the study is to model the variance in a dependent variable as a function of space, or lag distance.
		The purpose of the proposed study is to explore the relationship between a disturbance event (prescribed burning and mowing) in grasslands and the distribution and abundance of predatory beetles and grasshoppers as described by mathematical models of spatial structure (e.g., spatial autocorrelation, semivariance, and kriging).
		Semivariance is more appropriate if the purpose of the study is to model the variance in a dependent variable as a function of space, or lag distance (Jongman et al.
	mathbio.truman.edu /research/mathbioprogram/geringdecock2 (2159 words)

	Semivariance - Wikipedia, the free encyclopedia
		In spatial statistics, the semivariance is described by
		The semivariance is calculated in the same manner as the variance but only those observations that fall below the mean are included in the calculation.
		The semivariance is an invalid measure for variability, precision and risk because the sum of squared differences between x and x + h is divided by n, the number of data in the set, but it ought to be divided by df(o) = 2(n − 1), the degrees of freedom for the first variance term (see Ref 2).
	en.wikipedia.org /wiki/Semivariance (428 words)

	12.747 Lecture 5 Section 3
		The semivariance is a curve (vector) derived from the data according to:
		The value of the semivariance as the lag (h) goes to infinity, it is equal to the total variance of the data set.
		The easiest semivariance model to envision of your data is when the sill and range values are always the same, regardless of the direction being considered.
	w3eos.whoi.edu /12.747/notes/lect05/l05s03.html (910 words)

	Geostatistics is based on the concept of random functions (RF), whereby the set of attribute values z(x) at all ...
		Semivariance is a measure of the degree of spatial dependence between samples.
		The plot of the semivariances as a function of distance from a point is referred to as a semivariogram or simple Variogram (as is called these days).
		The semivariance increases as the distance increases until at a certain distance away from a point the semivariance will equal the variance around the average value, and will therefore no longer increase, causing a flat region to occur on the semivariogram called a sill.
	plaza.ufl.edu /slamsal/Links/Academics/Geostatistics_introduction.htm (1129 words)

	Three-Tiered LTMO Section 6 - Spatial Statistical Evaluation
		Fundamental to geostatistics is the concept of semivariance [g(h)], which is a measure of the spatial dependence between sample variables (e.g., chemical concentrations) in a specified direction.
		For h = 0, for example, a sample is being compared with itself, so normally g(0) = 0 (the semivariance at a spacing of zero, is zero), except where a so-called nugget effect is present (Figure 6.1), which implies that sample values are highly variable at distances less than the sampling interval.
		Fitting a theoretical model to calculated semivariance points is accomplished by trial-and-error, rather than by a formal statistical procedure (Davis, 1986; Clark, 1987; Rock, 1988).
	www.stanley.army.mil /Volume5/LTMO/Section6.htm (1885 words)

	[No title]
		Semivariance is measured for a specific orientation and gives a measure of the degree of spatial dependence of the variable along this orientation.
		The usual way to represent the relationship between semivariance and distance is in the form of a semivariogram, where semivariance is the Y axis and h (distance) is represented on the X axis.
		The results from the geostatistical analysis indicate that the range values seem to be stabilizing at around 6 to 10 metres as the semivariance decreases from 950 at 500 feet to 220 at 2500 feet in altitude.
	www.sfu.ca /rs/spatial/stein.htm (1364 words)

	Geog 460: GIS Analysis
		Semivariance measures how elevation values are similar to the values in neighbors.
		Larger semivariance values mean that values are less similar while smaller semivariance values means that values are more similar to each other.
		Thus, semivariance is a measure of the interdependency of the elevational values based on spatial proximity.
	gis.depaul.edu /shwang/teaching/geog460/lec13.htm (797 words)

	Proposal
		However, the parameters of sill, range, nugget and spatial anisotropy are still important in the procedure of determining the sizes of moving window and lag distance to be used to compute the essential semivariance.
		Practically, the semivariance values are assigned to the central pixel of the moving window.
		Pseudo-cross variogram, which represents the semivariance of the cross increments instead of the covariance of the direct increments as in equation (4).
	www-personal.umich.edu /~danbrown/nre543/tzhao.html (2248 words)

	Semivariance (Site not responding. Last check: 2007-11-07)
		Hi, Was wondering if anyone of you can answer that whether this formula is correct: Semivariance only uses the returns below the mean (in the numerator).
		It should only consider the variances that fall short of the target but the denominator is actually either N or (N-1), where N is the total number of observation.
		So, the formula for Semivariance should be: sum [(X(i) - Target) ^ 2 ] {for X(i) below the target} / (N - 1) (where N is the total observation) It seems that the Glossary here is showing that you should have only the number of observations that fall below the mean in the denominator.
	www.contingencyanalysis.com /archive/archive03-2/000000b1.htm (109 words)

	semivariograms
		The Semivariance cloud is a graph of the semivariances for all pairs of points within the Pair Search Range defined in the Semivariogram Parameters (or calculated by EVS’s expert system).The formula to calculate Semivariance for any given pair of points at locations i and j is:
		For this case, what is plotted is one-half of the squares of the differences (semivariance) and vector distance of the pairs.
		When the semivariance is plotted, the total length of lines above the surface and below should be equal.
	www.ctech.com /evs_help/workbooks/workbook_11__c_tech_geostatistics/semivariograms.htm (1130 words)

	Esteban Danna
		The closer the dataset is to a straight line, the closer it is to following a normal distribution.
		A sill represents the maximum value reached in the semivariance in a variogram.
		A nugget represents the intersection between the semivariance and the y axis.
	www.csun.edu /~emd43078/Lab7.htm (523 words)

	Geostatistics for the Environmental Sciences - GS+ Overview
		Widely praised, GS was the first geostatistics package to offer all components — from semivariance analysis through kriging and mapping — in an integrated package that provides the flexibility demanded by the specialist and the simplicity needed by the novice.
		Variograms that appear in the Semivariance Analysis window — both isotropic and anisotropic — can be enlarged into their own windows, from which values and graphs can be printed, and from which each point along the curve can be decomposed into the pairs of points on which it is based.
		Maps of semivariance in every compass direction (the center marks the origin of each variogram) allow the axis of maximum variation to be easily identified.
	www.exetersoftware.com /cat/gs7/index.html (1062 words)

	methods SA
		Semivariance describes the average squared differences in depth at a given sampling scale (lag).
		When semivariance is graphed as a function of lag, semivariance typically increases with lag to a maximum value and then plateaus.
		A 3 x 3 cm area of each canopy was scanned with a Replica 3D scanner with Reversa 25 optics hardware, resulting in a maximum of 13,077 depth points.
	www1.union.edu /rices/claudia_web/methods_sa.htm (313 words)

	The Gateway Fund: What's New
		That's why semivariance, an alternative risk measure already used by many pension managers, is gaining favor at some fund companies.
		But for now, it is difficult for individuals to factor semivariance into fund selection.
		Morningstar, Inc., for example, uses semivariance to calculate its risk ratings and influential star ratings, but doesn't reveal funds' semivariances separately.
	www.gatewayfund.com /news_forbes.asp (1210 words)

	CFA Level 1 - Statistical Concepts And Market Returns - Standard Deviation And Variance
		Semivariance is a risk measure that focuses on downside risk, and is defined as the average squared deviation below the mean.
		Computing a semivariance starts by using only those observations below the mean, that is, any observations at or above the mean are ignored.
		The idea behind semivariance is to focus on negative outcomes.
	www.investopedia.com /study-guide/cfa-exam/level-1/quantitative-methods/cfa10.asp (1571 words)

	Michael M Fuller, Invasive Species
		Variograms shows the change in semivariance, computed for two samples, with increasing distance between samples.
		Semivariance is a measure of the difference in the samples: the more similar two samples are, the lower the semivariance.
		In an omnidirectional variogram the semivariance is calculated for all pairwise combinations of samples and the average is then reported for each of several distance lags.
	www.tiem.utk.edu /~mmfuller/WebDocs/HTMLfiles/spatial_tab.html (532 words)

	GIP Lab -
		The semivariance at the range approximates the variance of each observation, while the semivariance at zero distance estimates measurement error.
		Technically, empirical semivariance equals half the average squared difference between pairs of observations that are separated by a given distance.
		Semivariogram: A plot of semivariances against separation distance; the empirical or sampling semivariogram estimates the population semivariogram—which can be used for kriging.
	inlet.geol.sc.edu /giplab/sop.htm (600 words)

	Learn more about Semivariance in the online encyclopedia. (Site not responding. Last check: 2007-11-07)
		Learn more about Semivariance in the online encyclopedia.
		In spatial statistics, semivariance can be described by
		A plot of the semivariance versus distance between data values is known as a semivariogram, or simply as a variogram.
	www.onlineencyclopedia.org /s/se/semivariance.html (168 words)

	Spatial Statistics Glossary
		- a user-specified distance class within which semivariance is computed for a set of data points.
		- the distance at which the maximum semivariance is attained by a transitive semi-variogram.
		Given two locations x and (x + h), a measure of one-half of the mean square differences (the semivariance) produced by assigning the value z(x + h) to the value z(x), where h (known as the lag) is the inter-sample distance.
	www.forestry.umt.edu /academics/courses/for503/stats_glossary.htm (782 words)

	PCB5937: One Dimensional Spatial Analysis-Part II
		The two most common structure functions are the semivariance (graphed as a semivariogram) and autocorrelation (as a correlogram).
		The sill is the value where the semivariance levels off, depicts the amount of variance
		The range is the distance at which the leveling occurs, depicts where autocorrelation occurs The nugget is the semivariance at a distance of 0.
	pegasus.cc.ucf.edu /~jweisham/pcb5937/1dpt2.htm (572 words)

	IngentaConnect Mean-Semivariance Efficient Frontier: A Downside Risk Model for P... (Site not responding. Last check: 2007-11-07)
		Accordingly, this paper searches for a stochastic programming model in which the portfolio semivariance is the objective function to be minimized subject to standard parametric constraints, which leads to the mean-semivariance efficient frontier.
		From this basis, the portfolio semivariance matrix form is strictly mathematically derived, thus an operational quadratic objective function is obtained without resorting to heuristics.
		Ease of computation is highlighted by a numerical example, which allows one to compare the results from the proposed mean-semivariance approach with those derived from the traditional mean-variance model.
	www.ingentaconnect.com /content/routledg/ramf/2005/00000012/00000001/art00001 (266 words)

	Kriging
		Samples measured close together tend to have a low semivariance, and samples measured far apart tend to have a high semivariance, eventually leveling off to a constant value.
		A semivariogram plots distance in the x-axis, and semivariance for the distance in the y-axis (PSU 2007).
		Lastly, we use these semivariances to solve a group of linear equations that will produce a result that minimizes the amount of error in the predicted measurement of the value.
	www.personal.psu.edu /students/g/w/gws149/GEOG_486/Lesson_5/Kriging.html (607 words)

	Kriging Extension for ArcView GIS (Site not responding. Last check: 2007-11-07)
		Specify all the required information, including semivariance model, Z field, cell size, distance of search, number of neighbors, and the file name of semivariance.
		That is, you don't have to specify this if you are not interested in semivariance.
		However, when you do need semivariance information, be sure to click the check box "Generate semivariance grid" to activate the "Semivariance file" and give a name to it.
	www.geocities.com /ncxiao/kriging.html (421 words)

	Variograms Window (Site not responding. Last check: 2007-11-07)
		Additionally, the semivariance values that were used to produce the variogram can be listed, and Variance Cloud Analysis and h-Scattergram Analysis can be performed.
		If you do not want parameters to appear as a footnote you must use the Edit Graph command to bring up the Graph Settings dialog and in the Footnote field remove the notation "(model results)".
		Bring up an Variogram Values Window, including for each lag class the average separation distance for pairs of points in that class, the average semivariance for those points, and the number of pairs of points upon which the average distance and semivariance are based.
	www.exetersoftware.com /cat/gs7/GSWinHelp/variograms_window.htm (239 words)

	Success and failure of agricultural futures contracts, how to best predict semivariance, and GARCH option pricing with ...
		Second, to determine the relative accuracy in predicting price and yield semivariance of three approaches namely, the method of moments, the normal approximation, and the Edgeworth expansion.
		Root mean squared errors and encompassing regression were used to assess the performance of each method.
		The Black option pricing model with implied volatility outperforms that of the GARCH in terms of forecasting actual option premia for options ranging from 21 to 50 days to maturity.
	e-archive.library.okstate.edu /dissertations/AAI9608931 (328 words)

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