PRIMER-e v7 生態學多變數統計軟體
- PRIMER-e v7 生態學多變數統計軟體
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類別統計分析軟體
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介紹PRIMER 已成為非參數多變量分析軟件工具的全球標準。當變量過多或多元正態性假設不成立時，經典技術會動搖。 PRIMER 使用統計方法進行救援，這些方法依賴於強大的置換技術進行嚴格的推理，通常根據用戶選擇的等級相似性執行。盡量減少你的假設。最大化您的洞察力。 第 7 版充滿了 PRIMER 獨有的大量新產品（例如 3 路 ANOSIM、 閾值度量 MDS、kRCLUSTER、引導程序平均值等），提供了 一個不可或缺的現代工具來可視化、分析和表徵多變量中的顯著模式數據。
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價格
PRIMER-e v7 生態學多變數統計軟體
Analyse ecological data, or any other data, that would benefit from a safe non-parametric approach.
PRIMER v7 provides a wide range of univariate, graphical and multivariate routines for analysing arrays of species-by-samples data from community ecology.
Data are typically of abundance, biomass, % area (or line) cover, presence/absence etc. and arise in biological monitoring of environmental impacts and more fundamental ecological studies. Also catered for are matrices of physical values and chemical concentrations, which are analysed in their own right or in parallel with biological assemblage data, e.g., to examine co-variation of biotic changes with physico-chemical conditions.
Though the analysis requirements for biological assemblage data are a principle focus, the package is equally applicable (and increasingly being applied) to other data structures which are multivariate or can be treated as such.
The unifying feature is that all datasets can be reduced to an appropriate triangular matrix representing the resemblance of every pair of samples in terms of their assemblages, suites of biomarkers, particle size distributions, shape of growth curves, etc. Clustering and ordination techniques are then able to display the relationships among samples, and permutation tests are used to test hypotheses.
Easy manipulation of data and results
The PRIMER Workspace (*.pwk)
• Work on multiple data-sets, graphics and output files
simultane ously within a single interactive & intuitive
graphical Windows environment.
• Keep track of all your work easily using the tree-like
navigation pane.
• Input/output data from Excel, .csv, .txt or 3-column
format.
• View and change the colours, fonts, look & feel of
your plots and graphics on-screen.
• Copy/print/export results to .jpg, .emf, .tif, .gif, .png,
.bmp or .rtf files.
• Power and flexibility in specifying analyses.
• Identify important subsets of samples or variables.
• Define group structures for tests and displays.
• Handle relatively large data sets (subject only to
available Windows memory).
• Merge or split data on specified criteria.
• Unleash the time-saving power of in-built Wizards
for matrix displays and core analyses.
Ordination
Ordination techniques for visualising data, including principal
components analysis (PCA), plus non-metric, metric or threshold
-metric multi-dimensional scaling (nMDS, mMDS, tmMDS).
Visualise high-dimensional data in 2d or 3d. Customise text,
colours and symbols. Add essential information with overlays,
such as clusters, trajectories, bubbles, images, vectors, or minimum spanning trees.
Use bootstrapping to show confidence regions on MDS plots.
Spin, expand, rotate, animate, save and share your insightful
images.
Clustering
Perform hierarchical clustering into sample (or variable/species) groups, with single, complete, group-average or flexible-beta
linkage options.
Create cophenetic distance matrices and plot dendrograms.
Customise, rotate, collapse, zoom in, or print them out over
multiple pages to capture all of the finer details.
Similarity profiles (SIMPROF) and associated permutation tests
identify the coherence of groups of samples or species.
Divisive clustering methods can be unconstrained (UNCTREE),
or constrained by environmental (or other) variables (LINKTREE), while krCLUSTER does a non-parametric version of k-means
clustering.
Shade plots and Heat maps
Display actual values in 2d or 3d with grey-scale or colour
spectra of choice.
Salient patterns are uncovered with ease.
Samples and variables can be sorted according to various
criteria, including gradients, clustering constraints, or groupings.
Labels and symbols are easily modified and customised
Non-parametric tests
Permutation-based hypothesis testing using analysis of
similarities (ANOSIM), which tests for differences between
groups of multivariate samples from different times, locations,
experimental treatments, etc. PRIMER’s algorithms now support most three-way designs for these fully non-parametric tests.
Identify species primarily providing discrimination between two
groups of samples (SIMPER).
Test for seriation and other Mantel-type tests for sequential data in time or space.
Relate matrices to one another or identify subsets of variables
which together produce a ‘BEST’ Mantel-type match to a given
resemblance matrix.
Permutation tests include variable-selection steps to ensure
rigorous statistical inference.
Biodiversity analyses
Use taxonomic, functional and/or phylogenetic information to
inform biodiversity assessments. Test against master lists using
sub-sampling algorithms.
Calculate a multitude of classic and novel diversity indices or
summary statistics of individual variables, with aggregation
tools for analysing data at higher taxonomic levels.
Access a wide choice of flexible plotting functions for individual
variables: line, histogram, scatter, bar, box, means, surface or
Draftsman plots.
Ecology-specific tools are at your fingertips, such as dominance
plots, geometric class plots, or abundance biomass curves (ABC).
Extensive manuals and examples
PRIMER version 7 includes context-specific Help buttons, as well as extensive downloadable manuals in searchable pdf format:
“Change in Marine Communities (3rd ed.)”, explaining all of the
statistical methods underlying the software in non-mathematical terms; and
“PRIMER v7: User Manual / Tutorial”, explaining precisely how to
implement the methods and all software utilities.
A large number of full genuine data sets are included with the
package so that the user can replicate analyses given in the
manual and authored scientific publications.
系統需求
Windows 10 (must be Windows XP or later). Note that PRIMER
will not run natively on Apple Mac OSX, but it is possible to use
it via virtualization software or Boot Camp.
CPU:
Modern Intel or AMD processor
RAM:
8 GB or more
Hard-disk space:
100 MB or more
PRIMER-e v7 生態學多變數統計軟體
分析可從安全的非參數方法中受益的生態數據或任何其他數據。
PRIMER V7提供了廣泛的單變量，圖形和多變量例程從社區生態學分析物種逐樣本數據的數組。 數據通常豐度，生物量，％面積（或線）蓋，存在/不存在等的並出現在環境影響的生物監測和更基礎的生態研究中。還提供物理值和化學濃度矩陣，這些矩陣可以單獨分析或與生物組合數據並行分析，例如，檢查生物變化與物理化學條件的共變。
儘管對於生物組合數據分析要求是一個原理焦點，所述包裝是同樣適用（和越來越多地應用），其是多變量或可被視為這樣的其它數據結構。 該統一特徵是，所有的數據集可以是簡化為一個合適的三角形矩陣，代表每對樣品在組合、生物標誌物套件、粒度分佈、生長曲線形狀等方面的相似性。然後聚類和排序技術能夠顯示樣品之間的關係，置換檢驗用於檢驗假設。
輕鬆處理數據和結果
PRIMER 工作區 (*.pwk)
• 在單個交互式直觀圖形 Windows 環境中同時處理多個數據集、圖形和
輸出文件。
• 使用樹狀導航窗格輕鬆跟踪您的所有工作。
• 來自 Excel、.csv、.txt 或 3 列格式的輸入/輸出數據。
• 在屏幕上查看和更改繪圖和圖形的顏色、字體、外觀和感覺。
• 將結果復制/打印/導出到 .jpg、.emf、.tif、.gif、.png、.bmp 或 .rtf
文件。
• 指定分析的能力和靈活性。
• 確定樣本或變量的重要子集。
• 定義測試和顯示的組結構。
• 處理相對較大的數據集（僅取決於可用的 Windows 內存）。
• 根據指定條件合併或拆分數據。
• 釋放用於矩陣顯示和核心分析的內置嚮導的省時功能。
排序
協調技術用於可視化數據，包括主成分分析（PCA），加上非十進制，度量或閾值度量的多維標度（NMDS，MMDS，tmMDS）。 在二維或三維可視化高維數據。自定義文本、顏色和符號。使用疊加添加基本信息，例如集群、軌跡、氣泡、圖像、向量或最小生成樹。
使用 bootstrapping 在 MDS 圖上顯示置信區域。旋轉、擴展、旋轉、動畫、保存和分享您有見地的圖像。
聚類
執行分級聚類成樣品（或可變/種）基團，具有單，完整，組平均的或柔性的-β鍵選項。 創建同表象距離矩陣和情節樹狀圖。自定義，旋轉，崩潰，放大，或打印出來在多個頁面來捕獲所有的細節。 相似的配置文件（SIMPROF）和相關的排列檢驗鑑定樣品或物種群的一致性。 分裂聚類方法可以不受約束 (UNCTREE)，也可以受環境（或其他）變量 (LINKTREE) 約束，而 krCLUSTER 執行 k 均值聚類的非參數版本。
陰影圖和熱圖
使用所選的灰度或色譜顯示 2d 或 3d 中的實際值。
凸圖案露出自如。 樣品和變量可以根據不同的標準，包括梯度，聚類約束或分組進行排序。
標籤和符號很容易修改和定制。
非參數檢驗
使用相似性分析 (ANOSIM) 的基於排列的假設檢驗，它檢驗來自不同時間、地點、實驗處理等的多變量樣本組之間的差異。PRIMER 的算法現在支持這些完全非參數檢驗的大多數三向設計。 確定物種主要提供兩組樣品（假笑）。之間的辨別 試驗系列化，在時間或空間上連續的數據的其它曼特爾型試驗。 相關矩陣彼此或識別的子集的變量一起產生與給定相似矩陣的“最佳”Mantel 類型匹配。 置換測試包括可變的選擇步驟，以確保嚴格的統計推斷。
生物多樣性分析
使用分類、功能和/或系統發育信息為生物多樣性評估提供信息。使用子採樣算法對主表測試。 計算經典和新穎的多樣性指數或單個變量的匯總統計，匯總工具在更高的分類級別分析數據，眾說紛紜。 訪問了廣泛的選擇靈活的繪圖功能各個變量：線，柱狀圖，散射，酒吧，框，裝置，表面或曲線繪圖員 生態特定工具唾手可得，諸如顯性圖，幾何類情節，或豐度的生物量曲線（ABC）。
大量的手冊和示例
底漆7版包括上下文特定的幫助按鈕，以及在搜索的PDF格式下載粗放手冊： “變化中的海洋生物群落（第三版）”，解釋所有的非數學術語軟件基礎的統計方法; 和 “引物V7：用戶手冊/教程”，恰恰說明如何實現的方法和所有的軟件工具。 大量的全正版的數據集所包含的包，以便用戶可以複製在給定的分析手冊和撰寫的科學出版物。
LISREL 11結構模式分析軟體
在過去的45年中，LISREL模型，方法和軟件已成為結構方程模型（SEM）的同義詞。但是，今天，LISREL不再局限於SEM。LISREL 10包括64位統計應用程序LISREL，PRELIS，MULTILEV，SURVEYGLIM和MAPGLIM。