如何在MATLAB中忽略NaN? [英] How to ignore NaNs in MATLAB?

问题描述

我正在寻找一种方法来忽略矩阵中的特定条目，以便随后在MATLAB中进行线性回归

I'm looking for a way to ignore specific entries in matrices for subsequent linear regression in MATLAB

我有两个矩阵:y =

I have two matricies: y =

    9.3335    7.8105    5.8969    3.5928
    23.1580   19.6043   15.3085    8.2010
    40.1067   35.2643   28.9378   16.6753
    56.4697   51.8224   44.5587   29.3674
    70.7238   66.5842   58.8909   42.7623
    83.0253   78.4561   71.1924   53.8532

和x =

    300   300   300   300
    400   400   400   400
    500   500   500   500
    600   600   600   600
    700   700   700   700
    800   800   800   800

我需要对y在20到80之间的点进行线性回归，因此我需要一种使过程完全自动化的方法.我尝试制作偏远的y值[及其对应的x值] NaN，但是在线性回归过程中，matlab在计算中包括了NaN，所以我得到了NaN输出.谁能建议一个忽略这些条目或完全忽略NaN的好方法? (请注意:y中的列通常具有不同的值组合，因此我无法消除整行).

I need to do linear regression on the points where y is between 20 and 80, so I need a way to fully automate the process. I tried making the outlying y values [and their corresponding x values] NaNs, but during linear regression, matlab included the NaNs in the calculations so I got NaN outputs. Can anyone suggest a good way to ignore those entries or to ignore NaNs completely calculations? (NOTE: the columns in y will often have different combinations of values, so I can't eliminate the whole row).

推荐答案

由于您分别在每一列上执行了回归，因此您可以简单地在具有有效y值的行中形成索引:

Since you perform your regression on each column separately, you can simply form an index into rows with the valid y-values:

nCols = size(x,2);

results = zeros(2,nCols);
validY = y>20 & y<80; %# a logical array the size of y with valid entries
nValid = sum(validY,1);

for c = 1:nCols
    % results is [slope;intercept] in each column
    results(:,c) = [x(validY(:,c),c),ones(nValid(c),1)]\y(validY(:,c),c);

end

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