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MVSP是多變量分析軟件，用于執(zhí)行各種排序和聚類分析。它為從生態(tài)學(xué)，地質(zhì)學(xué)到社會學(xué)和市場研究等領(lǐng)域的數(shù)據(jù)分析提供了一種簡便的方法。 MVSP正在數(shù)百個地點使用。使用MVSP進(jìn)行分析的結(jié)果已經(jīng)發(fā)表在許多期刊上，包括“科學(xué)”，“自然”，“生態(tài)學(xué)”，“石油地質(zhì)學(xué)雜志”和“生物地理學(xué)雜志”。
分析完數(shù)據(jù)后，你可以直接繪制結(jié)果。選擇要查看的排序軸，并繪制散點圖。聚類分析結(jié)果的樹狀圖是自動生成的。這些圖表可以打印在輸出設(shè)備上。
MVSP執(zhí)行多種類型的根分析排序：主成分分析（PCA），主坐標(biāo)分析（PCO）和對應(yīng)/分析（CA/DCA）。他執(zhí)行規(guī)范對應(yīng)分析（CCA），這是生態(tài)學(xué)研究中流行的技術(shù)。您還可以使用23種不同的距離或相似性度量以及7種分組策略執(zhí)行聚類分析。可以分析的案例和變量的數(shù)量僅受Windows可用內(nèi)存（RAM和硬盤交換文件）的限制，至多20億個案例和變量。
桌面
MVSP使用KCS桌面隱喻。在學(xué)習(xí)數(shù)據(jù)，統(tǒng)計結(jié)果和圖表時，您可以在自己面前擴(kuò)展它們，就像在桌上寫字一樣。它還有一個筆記本，您可以在其中寫下想法和觀察結(jié)果。嘗試新的圖形，添加新的數(shù)據(jù)，檢查結(jié)果，打印或保存所需的內(nèi)容。
嘗試新圖形，添加新數(shù)據(jù)，細(xì)讀結(jié)果，然后打印或保存所需的圖形。退出MVSP時，您可以將窗口的位置和內(nèi)容保存在桌面上。以后您可以將其還原到相應(yīng)狀態(tài)。MVSP使您可以從上次中斷的地方接機(jī)?？梢詾椴煌捻椖勘４娑鄠€桌面。
分析數(shù)據(jù)后，您可以直接繪制結(jié)果。選擇要查看的排序軸，將繪制散點圖?？梢詫⒂糜谧兞康膱D形和用于CA結(jié)果的案例組合在一起?？梢陨蒔CA結(jié)果的歐幾里德雙曲線（帶有變量，例如矢量），以及CCA中的環(huán)境變量的雙曲線。也可以為PCA，PCO和CA/CCA創(chuàng)建卵石圖。還可以創(chuàng)建原始變量的散點圖，以及匯總變量的箱形圖和胡須圖。
描述
數(shù)據(jù)矩陣處理：將數(shù)據(jù)轉(zhuǎn)置，轉(zhuǎn)換（可用的轉(zhuǎn)換包括以10為底的對數(shù)，e和2，平方根，Aitchison的數(shù)據(jù)），轉(zhuǎn)換為比例，標(biāo)準(zhǔn)分?jǐn)?shù)，八度音階或范圍通過地層研究的格式，可以選擇行和列刪除
數(shù)據(jù)導(dǎo)入和導(dǎo)出：Lotus 1-2-3和Symphony和Cornell生態(tài)計劃
主坐標(biāo)分析，執(zhí)行以下選項：使用任何類型的輸入度矩陣，用戶定義的值和度
主成分分析，具有以下選項：相關(guān)或協(xié)方差矩陣，居中或非中心分析，用戶定義的值，Kaiser和Jolliffe的平均值規(guī)劃，用戶自定義的度水平
對應(yīng)分析，具有以下選擇：Hill的細(xì)分趨勢，分析或倒數(shù)平均算法的選擇，罕見或常見分類群的加權(quán)和縮放，用戶定義的值和度水平。
歐幾里得，標(biāo)準(zhǔn)歐幾里德，余弦（或標(biāo)準(zhǔn)歐幾里得），曼哈頓度量，堪培拉度量，和弦，卡方，平均和平均字符差距等十九種不同的度和距離度量。 Pearson乘積矩相關(guān)和Spearman秩相關(guān)系數(shù);度和高爾的系數(shù); Sorensen、Jaccard的匹配，Yule和Nei的二進(jìn)制系數(shù)。
聚類分析，具有以下選擇：七種策略（UPGMA，WPGMA，中位數(shù)，質(zhì)心），約束聚類，其中保持輸入順序（例如地層研究），隨機(jī)輸入順序，積分樹狀圖生產(chǎn)。-獨立的應(yīng)用程序允許數(shù)據(jù)矩陣按樹狀圖的順序排序;允許在數(shù)據(jù)中看到模式。
多樣性指數(shù)有以下選項：辛普森指數(shù)，香農(nóng)指數(shù)或布里淵指數(shù)，還可以計算出對數(shù)基數(shù)，均勻度和物種數(shù)量的選擇。
MVSP是可以執(zhí)行一些數(shù)值分析的程序。這些可以用于許多科學(xué)領(lǐng)域。它還可以計算幾種分析法則，包括主坐標(biāo)，對應(yīng)/去趨勢對應(yīng)分析和主坐標(biāo)。該程序可以執(zhí)行具有不同距離和相似性度量以及聚類策略的聚類分析。借助其雙重聚類選項，用戶可以在一個步驟中生成大小寫和變量的某些樹狀圖。原始數(shù)據(jù)矩陣可以按照與它們的樹狀圖的順序排列。可以執(zhí)行約束聚類，因此可以保持原始輸入數(shù)據(jù)的順序。
但是，可以分析的大小寫和變量的數(shù)量于Windows計算機(jī)（硬盤和RAM交換文件）上的內(nèi)存量。MVSP提供了幾種數(shù)據(jù)處理功能。這些功能包括轉(zhuǎn)換，合并數(shù)據(jù)文件以及轉(zhuǎn)換為不同類型的格式。數(shù)據(jù)也可以導(dǎo)出多種格式。
功能：
易于使用，具有現(xiàn)代Windows界面（可配置工具欄，上下文菜單，菜單結(jié)構(gòu)）
用于定義的選項會自動保存以備將來使用
可保存的桌面；您可以將當(dāng)前分析會話中的結(jié)果，圖形和注釋保存到磁盤，然后稍后將其還原以恢復(fù)到上次中斷的位置。
無限數(shù)量的變量和大小寫（僅受可用的Windows內(nèi)存（包括RAM和硬盤交換文件））。
數(shù)據(jù)矩陣處理：
內(nèi)置類似電子表格的數(shù)據(jù)編輯器；包括多類撤消功能，行和列的刪除和插入。
矩陣轉(zhuǎn)置
數(shù)據(jù)轉(zhuǎn)換，使用對數(shù)以10，e和2為平方根，對數(shù)數(shù)據(jù)的Aitchison對數(shù)和標(biāo)準(zhǔn)化?？梢赃x擇各個變量進(jìn)行轉(zhuǎn)換。
轉(zhuǎn)換成地層范圍格式
可以將個案分配給預(yù)先指定的組；然后將這些顯示在結(jié)果和圖形上
將多個數(shù)據(jù)文件合并為一個
數(shù)據(jù)導(dǎo)入和導(dǎo)出；Lotus 1-2-3和Symphony，Excel，Quattro，xBase，Paradox，SIMSTAT，純文本和Cornell生態(tài)程序
通過使用“導(dǎo)入預(yù)覽”對話框，簡化了導(dǎo)入過程；使您可以預(yù)覽導(dǎo)入的數(shù)據(jù)并更改選項以獲得成功
分析：
易于選擇要納入分析的變量和案例；無需修改原始數(shù)據(jù)
主成分分析，具有以下選項：相關(guān)性或協(xié)方差矩陣，居中或無中心分析，用戶定義的要提取的軸數(shù)，包括平均值的Kaiser和Jolloffe規(guī)則。
使用以下選項執(zhí)行的主坐標(biāo)分析：使用類型的輸入性矩陣，用戶定義的軸數(shù)來提取和精度。
對應(yīng)分析，具有以下選項：Hill的分段分解，選擇循環(huán)Jacobi或倒數(shù)平均算法，對或常見分類單元進(jìn)行加權(quán)并縮放，用戶定義的要提取的軸數(shù)和精度，用于表示案例的替代縮放比例的選擇與變量。
規(guī)范對應(yīng)分析（Canonical Correspondence Analysis）是在生態(tài)學(xué)研究中流行的一種技術(shù)，用于將環(huán)境變量納入物種分布的排序。
圖形：
原始數(shù)據(jù)中變量的散點圖（2-d和3-d）
原始數(shù)據(jù)的箱形圖和晶須圖
PCA，PCO和CA/CCA的散點圖（2-d和3-d）
CA/CCA結(jié)果的聯(lián)合圖（變量和案例的散點圖）
歐幾里德雙曲線（以變量繪制為矢量的情況的散點圖）的PCA結(jié)果
CCA雙曲線，環(huán)境變量為矢量，或名義變量為質(zhì)心
PCA，PCO和CA/CCA結(jié)果的值的Scree圖
散點圖上的點可以通過單擊點來識別，也可以將標(biāo)簽應(yīng)用于點
將案例分配給組時，散點圖為組顯示不同的符號，用戶可以使用自已定義的符號和顏色
聚類結(jié)果的樹狀圖（基于圖形和基于文本）
放大圖表以更仔細(xì)的查看區(qū)域
可定制；可以修改字體，標(biāo)題，顏色，背景樣式，軸縮放比例和位置，散點圖符號的類型和顏色。保存位置以供將來使用
將圖形另存為BMP或WMF文件，或復(fù)制到Windows剪貼板以傳輸?shù)狡渌绦?/p>
英文簡介：
MVSP is an inexpensive yet powerful multivariate analysis program for PC compatibles that performs a variety of ordination and cluster analyses. It provides an easy means of analyzing your data in fields ranging from ecology and geology to sociology and market research. MVSP is in use at hundreds of sites in over 50 countries. The results of analyses using MVSP have been published in numerous journals, including Science, Nature, Ecology, Journal of Petroleum Geology, and Journal of Biogeography.
Once your data have been analyzed you can plot results directly. Select the ordination axes you want to see and scattergrams will be drawn. Dendrograms of cluster analysis results are produced automatically. These graphs can then be printed on a variety of output devices.
DESCRIPTION
Data matrix manipulation: data may be transposed, transformed (transformations available include logarithms to base 10, e, and 2, square root, and Aitchison’s logratio for percentage data), converted to percentages, proportions, standard scores, octave class scale, or range through format for stratigraphic studies, and rows and columns may be selected for deletion
Data import and export; Lotus 1-2-3 and Symphony and Cornell Ecology Programs
Principal Coordinates Analysis, performed with the following options: use any type of input similarity matrix, user defined minimum eigenvalues and accuracy level
Principal Components Analysis, with the following options: correlation or covariance matrix, centered or uncentered analysis, user defined minimum eigenvalues, including Kaiser’s and Jolliffe’s rules for average eigenvalues, user defined accuracy level.
Correspondence Analysis, with these options: Hill’s detrending by segments, choice of eigenanalysis or reciprocal averaging algorithm, weighting of rare or common taxa and scaling to percentages, user defined minimum eigenvalues and accuracy level.
Nineteen different similarity and distance measures, including Euclidean, squared Euclidean, standardized Euclidean, cosine theta (or normalized Euclidean), Manhattan metric, Canberra metric, chord, chi-square, average, and mean character difference distances; Pearson product moment correlation and Spearman rank order correlation coefficients; percent similarity and Gower’s general similarity coefficient; Sorensen’s, Jaccard’s, simple matching, Yule’s and Nei’s binary coefficients.
Cluster analysis, with the following options: seven strategies (UPGMA, WPGMA, median, centroid, nearest and farthest neighbor, and minimum variance), constrained clustering in which the input order is maintained (e.g. stratigraphic studies), randomized input order, integral dendrogram production. Separate utility program allows data matrices to be sorted in the order of the dendrograms; allows patterns to be seen in the data.
Diversity indices, with the following options: Simpson’s, Shannon’s, or Brillouin’s indices, choice of log base, evenness and number of species can also be calculated.
Other Features
MVSP offers various data manipulation features, such as transformation, merging of two or more data files, and conversion to formats such as range-through. Data can be imported from and exported to a variety of formats, including Lotus 1-2-3, Excel, Quattro, xBase, Paradox, Cornell Ecology Program format and various plain text files.
Individual data cases can be assigned to groups. The group names are then printed on output and dendrograms, and the groups are depicted on scatterplots as different symbols. A fully customizable toolbar is available. Also, the data editor and other windows have multiple level undo, letting you reverse any changes you have made in the current session.
Features of MVSP
Easy to use, with modern Windows interface(configurable toolbar, context menus, simple menu structure).
Numerous user-defined options that are automatically saved for future use.
Saveble desktop;you can save all the results, graphs and notes of the current analysis session to disk, then restore them later to resume where you left off
Unlimited number of variables and cases(restricted only by available Windows memory, including both RAM and hard disk swap file).
Data matrix manipulation:
Built in spreadsheet-like data editor; includes full multievel undo capabilities, row and column deletion and insertion
Transposition of matrix
Transformation of data, using logarithms to base 10,e, and 2, square root, Aitchison's logratio for percentage data, and standardization.
Individual variables may be selected for transformation
Conversion to range through format for stratigraphic studies
Merging of several data files into one
Data import and export; Lotus 1-2-3 and Symphony, Excel, Quattro, xBase, Paradox, SIMSTAT, plain text and Cornell Ecology Programs.
Import process eased by the use of the Import Preview dialog;lets you preview the imported data and change options to ensure successful results
Analyses:
Easy selection of variables and cases to include in analysis; no need to modify original data
Principal Components Analysis, with the following options:correlation or covariance matrix, centred or uncentred analysis, user defined number of axes to extract, including Kaiser's and Jolliffe's rules for average eigenvalues, user defined number of axes to extract and accuracy level.
Correspondence Analysis, with these options:Hill's detrending by segments, choice of cyclic Jacbi or reciprocal averaging algorithm, weighting of rare of common taxa and scaling to percentages, user defined number of axes to extract and accuracy level, choice of alternative scalings for representing cases vs. variables.
Canonical Corespondence Analysis, a technique highly popular in ecological studies for incorporating environmental variables into an ordination of species distribuyions.
Twenty three different similarity and distance measures, including Euclidean, squared Euclidean, standardized Euclidean, cosine theta(or normalized Euclidean), Manhattan metric, Canberra metric, Bray Curtis, chord, aquared chord, chi-square and mean character difference distances; Pearson product moment correlation and Spearman rank order correlation coefficients; Percent similarity, modified, Morisita's similarity and Gower's general similarity coeffcient; Srensen's, Jaccard's simple matching, Yule's Nei's and Baroni-Urbani-Buser's binary coefficients.
Cluster analysis, with the following options: seven strategies(UPGMA, WPGMA,median, centroid mearest and fathest neighbour, and minimum variance), constrained clustering in which the input order is maintained(e.g. stratigraphic studies), randomized input order, integral dendrogram production. Dual clustering of both variables and cases with a sorted data matrix being produced; allows patterns to be seen in the data.
Diversity incices, with the following options:Simpson's Shannon's or Brillouin;s indices, choice of log base, evenness and number of species also calculated.
Graphcs:
Scatterplots(2-d and 3-d) of variables in raw data
Box and whisker plots of raw data
Scatterplots(2-d and 3-d) of PCA, PCO and CA/CCA results
Joint plots(scatterplot of cases with variables plotted as vectors) of PCA results
CCA biplots, with environmental variables ad vectors or, for nominal variables, as centroids
Scree plots of eigenvalues from PCA, PCO and CA/CCA results
Dendrograms of clustering results (both graphic and text-based)
Points on scatterplot can be identified by clicking on point. Also can have labels applied to all points
Zoom in on graphs to views specific areas more closely
Fully customizable: can modify, titles, coloues, background style, axis scalling and placement, type and colour of scatterplot symbol. All settings saved for future use
Save graphs as BMP or WMF files, or copy to windows clipboard for transfer to other programs.
