PhotoMetrix PRO
Colorimetric analysis in mobile devices [ http://goo.gl/WOuvGZ ]
What's PhotoMetrix PRO APK?
PhotoMetrix PRO is a app for Android, It's developed by GHELFER.NET Inc. author.
First released on google play in 6 years ago and latest version released in 6 months ago.
This app has 6.6K download times on Google play
This product is an app in Education category. More infomartion of PhotoMetrix PRO on google play
This app was created in 2014 and employs Single Linear Correlation technics for univariate analysis, Principal Component Analysis (PCA) and HCA for multivariate exploratory analysis and Partial Least Squares (PLS) for multivariate calibration. The image data are acquired using the device main camera and converted in RGB histograms. In addition, apart color channels of RGB, HSV, HSL and HSI systems are used during the univariate and multivariate processing. It is possible to send by e-mail the image data, analysis data and charts. In order to validate the obtained results, the same sets of data were tested using Microsoft Excel© and ChemoStat©. The results in both applications coincided in various combinations.
This app calculates: eigenvalues, eigenvectors, scores, loadings, latent variables, RMSEP, REMSEC, REMSECV using Singular Value Decomposition and other statistical methods in Multivariate Analysis .
Also calculates: slope (span), intercept (off-set) and regression (Pearson product-moment correlation coefficient) in Univariate Calibration Analysis.
Also available in iOS and Windows Phone.
https://dx.doi.org/10.5935/0103-5053.20160182
https://doi.org/10.1002/cem.3251
This app calculates: eigenvalues, eigenvectors, scores, loadings, latent variables, RMSEP, REMSEC, REMSECV using Singular Value Decomposition and other statistical methods in Multivariate Analysis .
Also calculates: slope (span), intercept (off-set) and regression (Pearson product-moment correlation coefficient) in Univariate Calibration Analysis.
Also available in iOS and Windows Phone.
https://dx.doi.org/10.5935/0103-5053.20160182
https://doi.org/10.1002/cem.3251
