Outlier removal from a matrix

RMOUTLIERS Remove outliers from data B = RMOUTLIERS(A) detects and removes outliers from data. A can be a vector, matrix, table, or timetable. If A is a vector, RMOUTLIERS removes the entries detected as outliers. If A is a matrix or a table, RMOUTLIERS detects outliers for each column and then removes the rows containing outliers. B = RMOUTLIERS(A,METHOD) specifies the method used to determine outliers. METHOD must be one of the following: 'median' (default), 'mean', 'quartiles', 'grubbs', or 'gesd'. B = RMOUTLIERS(A,'percentiles',[LP UP]) detects as outliers all elements which are below the lower percentile LP and above the upper percentile UP. LP and UP must be scalars between 0 and 100 with LP <= UP. B = RMOUTLIERS(A,MOVMETHOD,WL) uses a moving window method to determine contextual outliers instead of global outliers. MOVMETHOD can be 'movmedian' or 'movmean'. B = RMOUTLIERS(...,DIM) reduces the size of A along the dimension DIM. Use DIM = 1 to remove rows and DIM = 2 to remove columns. RMOUTLIERS(A,DIM) first calls ISOUTLIER(A) to detect outliers. B = RMOUTLIERS(...,'MinNumOutliers',N) removes rows (columns) that contain at least N outliers. N must be an integer. By default, N = 1. B = RMOUTLIERS(...,'ThresholdFactor',P) modifies the outlier detection thresholds by a factor P. See the documentation for more information. B = RMOUTLIERS(...,'SamplePoints',X) specifies the sample points X representing the location of the data in A for the moving window methods 'movmedian' and 'movmean'. If the first input A is a table, X can also specify a table variable in A. B = RMOUTLIERS(...,'MaxNumOutliers',MAXN) specifies the maximum number of outliers for the 'gesd' method only. B = RMOUTLIERS(...,'OutlierLocations',INDOUTLIER) specifies the outlier locations according to the logical array INDOUTLIER. Elements of INDOUTLIER that are true indicate outliers in the corresponding element of A. INDOUTLIER must have the same size as A. [B,INDRM,INDOUTLIER,LTHRESH,UTHRESH,CENTER] = RMOUTLIERS(...) also returns a logical column (row) vector INDRM indicating which rows (columns) of A were removed, a logical array INDOUTLIER indicating the location of the detected outliers, and the lower threshold, upper threshold, and center value used by the outlier detection method. Arguments supported only for table inputs: B = RMOUTLIERS(...,'DataVariables',DV) removes rows (variables) according to outliers in table variables DV. The default is all table variables in A. DV must be a table variable name, a cell array of table variable names, a vector of table variable indices, a logical vector, a function handle that returns a logical scalar (such as @isnumeric), or a table vartype subscript. Examples: % Remove outliers from a vector a = [1 2 1000 3 4 5] b = rmoutliers(a) % Remove only the rows which contain at least 2 outliers A = [[1 2 1000 3 4 5]', [1 2 1000 3 4 1000]'] [B,removedRows,outlierLocs] = rmoutliers(A,'MinNumOutliers',2) See also ISOUTLIER, FILLOUTLIERS, RMMISSING, ISMISSING, FILLMISSING Documentation for rmoutliers doc rmoutliers Other uses of rmoutliers gpuArray/rmoutliers tall/rmoutliers