Initially install R program and launch them on your operate system, then paste the following command in the R console to installing cran-vegan:

install.packages(pkgs=c("BiodiversityR", "vegan", "Rcmdr", "MASS", "mgcv", "cluster", "RODBC", "rpart", "effects", "multcomp", "ellipse", "maptree", "sp", "splancs", "spatial", "akima", "nnet", "dismo", "raster", "rgdal", "bootstrap", "PresenceAbsence", "maxlike", "gbm", "randomForest", "gam", "earth", "mda", "kernlab", "e1071", "glmnet", "sem", "rgl", "relimp", "lmtest", "leaps", "Hmisc", "colorspace", "aplpack", "abind", "XLConnect", "car", "markdown", "knitr", "geosphere", "maptools", "rgeos", "ENMeval", "red"), dependencies=c("Depends", "Imports"))

Best,

Saeed

Devendra Solanki

As par my knowledge and understanding, you may use SPSS or you should consult some videos from Youtube for cluster analysis software in detail.

The methods used in this text are OUTSTANDING: https://www.bing.com/search?q=Finding+groups+in+Data&pc=U528&form=QBLH&sp=-1&pq=finding+groups+in+data&sc=1-22&qs=n&sk=&cvid=08345E5BAFBA466BAEFD75C419F443F1

They are available in R see: https://rdrr.io/cran/cluster/

R is open source freeware: this link will get you started: http://sgpwe.izt.uam.mx/files/users/uami/gma/R_for_dummies.pdf

Use videos are here: https://www.bing.com/search?FORM=U528DF&PC=U528&q=R+Package+Cluster+videos

I have used these methods for over 20 years and they are great.

Best wishes, David Booth

PS This link is very useful: https://b-ok.cc/book/669277/d2cf59

if you send me the data, I can try. If possible , I will let You know and give you advice on the software and the method on which it is based. http://lc.kubagro.ru/

As a method of the research we used Automated system-cognitive analysis (ASC-analysis), which is a new innovative method of artificial intelligence: it also has its own software tool – an intelligent system called "Eidos" (open source software).

The Eidos-X++ system differs from other artificial intelligence systems in the following parameters:

- was developed in a universal setting, independent of the subject area. Therefore, it is universal and can be applied in many subject areas (http://lc.kubagro.ru/aidos/index.htm);

- is in full open free access (http://lc.kubagro.ru/aidos/_Aidos-X.htm), and with the relevant source texts (http://lc.kubagro.ru/__AIDOS-X.txt);

- is one of the first domestic systems of artificial intelligence of the personal level, i.e. it does not take special training in the field of technologies of artificial intelligence from the user (there is an act of introduction of system "Eidos" of 1987) (http://lc.kubagro.ru/aidos/aidos02/PR-4.htm);

- provides stable identification in a comparable form of strengh and direction of cause-effect relationships in incomplete noisy interdependent (nonlinear) data of very large dimension of numerical and non-numerical nature, measured in different types of scales (nominal, ordinal and numerical) and in different units of measurement (i.e. does not impose strict requirements to the data that can not be performed, and processes the data that is);

- contains a large number of local (supplied with the installation) and cloud educational and scientific applications (currently 31 and 200, respectively) (http://lc.kubagro.ru/aidos/Presentation_Aidos-online.pdf);

- provides multilingual interface support in 51 languages. Language databases are included in the installation and can be replenished automatically;

- supports on-line environment of knowledge accumulation and is widely used all over the world (http://aidos.byethost5.com/map5.php);

- the most time-consuming computationally, the operations of the synthesis models and implements recognition by using graphic processing unit (GPU) that some tasks can only support up to the solution of these tasks is several thousand times that really provides intelligent processing of big data, big information and big knowledge;

- provides transformation of the initial empirical data into information, and its knowledge and solution using this knowledge of classification problems, decision support and research of the subject area by studying its system-cognitive model, generating a very large number of tabular and graphical output forms (development of cognitive graphics), many of which have no analogues in other systems (examples of forms can be found in: http://lc.kubagro.ru/aidos/aidos18_LLS/aidos18_LLS.pdf);

- well imitates the human style of thinking: gives the results of the analysis, understandable to experts on the basis of their experience, intuition and professional competence.

R is already suggested, so I will just suggest some other programs:

https://www.gnu.org/software/pspp/

https://www.cs.waikato.ac.nz/ml/weka/

Thank you so much for your time and support...I've already downloaded the suggested software and learning it for now.

Hi,

You can try r-cran-vegan package using vegdist function on R program. Vegan is such a useful package for these analyses.

Best regards,

Saeed

Initially install R program and launch them on your operate system, then paste the following command in the R console to installing cran-vegan:

install.packages(pkgs=c("BiodiversityR", "vegan", "Rcmdr", "MASS", "mgcv", "cluster", "RODBC", "rpart", "effects", "multcomp", "ellipse", "maptree", "sp", "splancs", "spatial", "akima", "nnet", "dismo", "raster", "rgdal", "bootstrap", "PresenceAbsence", "maxlike", "gbm", "randomForest", "gam", "earth", "mda", "kernlab", "e1071", "glmnet", "sem", "rgl", "relimp", "lmtest", "leaps", "Hmisc", "colorspace", "aplpack", "abind", "XLConnect", "car", "markdown", "knitr", "geosphere", "maptools", "rgeos", "ENMeval", "red"), dependencies=c("Depends", "Imports"))

Best,

Saeed

In some situation this web tool can be handy too: Clustvis - a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap - https://biit.cs.ut.ee/clustvis/

Maybe it can be helpful:

1) R Tutorial - Classification Analysis (Bray-Curtis similarity index calculation and visualization application in R): http://ecovirtual.ib.usp.br/doku.php?id=en:ecovirt:roteiro:comuni:comuni_classr

2) FigTree (http://tree.bio.ed.ac.uk/software/figtree) to visualize dendograms. Some examples of applications:

• [1] https://ourcodingclub.github.io/tutorials/data-clustering/, with FigTree and the R library "vegan", this package has already been precisely indicated in the above messages.
• [2] with the R library "vegan3d": https://rpubs.com/fmobegi/458983 (https://rdrr.io/cran/vegan3d/) .

3) ELKI is an open source data mining software with an emphasis on unsupervised methods in cluster analysis: https://elki-project.github.io/tutorial/#basic-usage-example. There is a BrayCurtisDistanceFunction: https://elki-project.github.io/algorithms/distances

4) "bokeh" is an interactive Data Visualization in Python: https://docs.bokeh.org/en/latest/docs/gallery.html#standalone-examples

https://drive.google.com/open?id=1Yl8zSXE8l28Orj1BqL_xJLacvu6lZcel

Go to the link and download the Setup + Crack file.

I suggest you XL-STATE and PCORD software, both are easy to learn.