抽样权重，指定为非负标量值向量。w 的长度必须等于要抽样的整数范围或 population 的长度。 向量 w 必须有至少一个正值。 如果 w 包含负值或 NaN 值，randsample 将显示一条错误消息。randsample 函数以与 w(i)/sum(w) 成正比的概率进行抽样。 通常，w 是概率向量。randsample 函数仅支持为有放回抽样指定 … If v is a scalar, samples from 1:v.. As an alternate to randperm, you can also use randsample from the statistics toolbox.. y = randsample(n,k) returns a k-by-1 vector y of values sampled uniformly at random, without replacement, from the integers 1 to n. Note that it is "without replacement" (by default). It looks like that's what you're asking for. There's a slightly different behavior for edge cases, like randi(0,0,1) (which errors) vs. randsample(0,0,true) (which outputs an empty array). Learn more about randperm, randsample, datasample, random sub sample vector You may want to try randseq (requires the Bioinformatics Toolbox). Remark on … It looks like that's what you're asking for. Which option should I use? Our implementation follows Efraimidis and Spirakis (2006). If you happen to be using R2011b, and have access to the Statistics Toolbox, you can also use the new datasample function: m = rand(10037,9); mnew = datasample(m,1000); I don't think you can replicate your first code block "the easy way" with a call to randsample. datasample random number generator randperm randsample vector. Learn more about random number generator, vector, randperm, randsample, datasample Whilst, randsample generates samples with or without replacement of the population: 1:5 in this case. As Andrew pointed out, randsample absolutely does do sampling without replacement, just not with weights. I would like to select randomly two values from my vector. The first code block generates P and I recursively. Function File: y = randsample (v, k, replacement=false [, w]) Elements sampled from a vector. randomly select different elements of a vector. Generally randsample has more features: it is able to handle a non-default RandStream, and weighting. In some cases the input of randsample is just redirected to randi. If you have the Statistics and Machine Learning Toolbox, you can use the randsample() function: y = randsample(n,k) returns a k-by-1 vector y of values sampled uniformly at random, without replacement, from the integers 1 to n. The sequence of numbers produced by randperm is determined by the internal settings of the uniform pseudorandom number generator that underlies rand, randi, randn, and randperm.To control that shared random number generator, use the rng function. MATLAB function datasample follows Wong and Easton (1980), which is also quite fast; note however that function datasample may be very slow if applied repetedly, for the large amount of time spent on options checking. I have a vector with twenty unique values from 1 to 20. MATLAB: Random selection of n values from a vector – which function should I use. So if you set k as length(x), it is equivalent to doing a random shuffle of the vector.. 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