统计phd所需要上的数学课

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anderson11
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小弟在美国某top30院校读统计MS,同时还打算double一个数学MS,之后准备申请统计phd。

想问下各位前辈,如果想申请统计phd,哪些数学课是推荐上的?

我目前在上, machine learning theory,computational stats, DOE, grad level的real analysis。
以前还上过undegrad-level real analysis, differential geometry, complex analysis, optimization, game theory, mathematical finance, stochastic processes (号称是phd level,同学90%是phd,但用的是Markov Chain by Norris,没有太多测度论的东西),multivariate stats analysis, linear model (on abstract inner product space, with intro to sparsity recovery), PhD-level mathematical statistics regression等课。

我还想上的数学课大概有 stochastic optimization, functional analysis, measure theoretical probability theory, numerical linear algebra, Hilbert space, PhD level ML theory (ECE), convex optimization (ECE), grad-level complex analysis, grad-level differential geometry.. 大家觉得这些课优先上哪些呢?谢谢各位!

另外,我目前在和一个教授做stochastic processes的研究(偏理论),同时跟一个另外一教授做high dimensional stats的reading course。我目前方向还没定,
但小弟比较菜,定位前100,有书读就行,所以统计(or IEOR)各个方向都可以接受。
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