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  2. Highest and best use - Wikipedia

    en.wikipedia.org/wiki/Highest_and_best_use

    The Highest and Best Use as vacant may be the same or different as the Highest and Best use as improved. For improved properties, the first analysis applied is the use of the property based on the assumption that the parcel is vacant. Then, the analysis focuses on the use that should be made of the property as it is currently improved.

  3. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    e. In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts ...

  4. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...

  5. Robust principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Robust_principal_component...

    Robust Principal Component Analysis (RPCA) is a modification of the widely used statistical procedure of principal component analysis (PCA) which works well with respect to grossly corrupted observations. A number of different approaches exist for Robust PCA, including an idealized version of Robust PCA, which aims to recover a low-rank matrix ...

  6. Sparse PCA - Wikipedia

    en.wikipedia.org/wiki/Sparse_PCA

    Sparse PCA. Sparse principal component analysis (SPCA or sparse PCA) is a technique used in statistical analysis and, in particular, in the analysis of multivariate data sets. It extends the classic method of principal component analysis (PCA) for the reduction of dimensionality of data by introducing sparsity structures to the input variables.

  7. Chi-square automatic interaction detection - Wikipedia

    en.wikipedia.org/wiki/Chi-square_automatic...

    Chi-square automatic interaction detection ( CHAID) [1] [2] [3] is a decision tree technique based on adjusted significance testing ( Bonferroni correction, Holm-Bonferroni testing ). The technique was developed in South Africa in 1975 and was published in 1980 by Gordon V. Kass, who had completed a PhD thesis on this topic.

  8. Factor analysis of mixed data - Wikipedia

    en.wikipedia.org/wiki/Factor_analysis_of_mixed_data

    In statistics, factor analysis of mixed data or factorial analysis of mixed data ( FAMD, in the French original: AFDM or Analyse Factorielle de Données Mixtes ), is the factorial method devoted to data tables in which a group of individuals is described both by quantitative and qualitative variables. It belongs to the exploratory methods ...

  9. Distributional data analysis - Wikipedia

    en.wikipedia.org/wiki/Distributional_data_analysis

    Distributional data analysis is a branch of nonparametric statistics that is related to functional data analysis. It is concerned with random objects that are probability distributions, i.e., the statistical analysis of samples of random distributions where each atom of a sample is a distribution. One of the main challenges in distributional ...