Right, this is known as the inverse variance weighting https://en.wikipedia.org/wiki/Inverse-variance_weighting.
You're right, thanks for pointing that out. I missed adding the reference: Kammler DW. A First Course in Fourier Analysis. 2nd ed. Cambridge University Press; 2008. Figure 1.19. This visualization of the relationships…
This tool is fantastic! I was able to generate a Fourier-Poisson cube [0] in about 10 minutes, and the UI is incredibly intuitive. The focus on commutative diagrams, rather than a free-form canvas, is a brilliant design…
Be careful, the weight of Algorithm A by Efraimidis and Spirakis cannot be interpreted as the inclusion probability, and thus cannot be used in survey sampling to construct the Horvitz–Thompson estimator. See "Remarks…
If the bus arrives on time, the arrival time would be [tau, 2 * tau, ..., N * tau]. One way to simulate "random" arrival time is to draw uniform points in the interval [0, N * tau]. It turns out the inter-arrival time…
Relevance: from the cited paper, the variance of the median estimator is proportional to 1/(n * f^2), where n is the sample size and f is the density at median. Two observations: 1. With sufficiently large n, you can…
Asymptotic properties of quantile estimators are widely studied [1]. The key is to have a sufficiently large sample size. [1] Bahadur, R. R. (1966). A note on quantiles in large samples. Annals of Mathematical…
My takeaway is to avoid mixing the frequentist and Bayesian approaches. Choose one method: either follow the frequentist approach and avoid early data analysis, or use the Bayesian approach to compute posterior…
I'm grateful for leetcode. Despite my background in electrical engineering, where I specialize in statistical signal processing, I never had the opportunity to delve into algorithm or data structure courses during my…
1/ I think you are referring to pushforward measure (https://en.wikipedia.org/wiki/Pushforward_measure): the random variable "pushes" the probability measure to its codomain. 2/ pdf requires a stronger condition: the…
Agree, this is great! I wonder if there're some ML equivalent sites that present topics in a modular way?
Maybe "Probability via Expectation" by Peter Whittle https://link.springer.com/book/10.1007/978-1-4612-0509-8 or "Infinite Dimensional Analysis" by Charalambos Aliprantis and Kim Border…
Just curious what are the deeper optimization topics you were hoping to see in the monograph?
Second this. Richard is a great lecturer. Highly recommend his lecture recordings. His winter 2019 lecture videos and materials can be found here: https://github.com/rmcelreath/statrethinking_winter2019
Unless you water them down like some populate science books, I don't understand how you can teach probability and statistics without calculus?
If I remember correctly the royalty was $7.5 per iPhone. Not sure how that alone contributes to the $150 price hike.
Or C-x * for calc-dispatch? I guess the point of this app is the input doesn't have to be precise. Not sure emacs can do that.
Yes but not directly. It is used in the Monte Carlo simulation part. In communication systems everything is complex :D
Last week I converted a simple side project in Python to Julia. It's a sequential Bayeisan estimation problem. A pleasant surprise that the Julia version runs 30x faster than the Python counter part. I am sure the…
Fascinating! Such a great demonstration of Julia's strength. I wish more academic papers are written in this fashion or include a tutorial-like/reproducible post like this.
Right, this is known as the inverse variance weighting https://en.wikipedia.org/wiki/Inverse-variance_weighting.
You're right, thanks for pointing that out. I missed adding the reference: Kammler DW. A First Course in Fourier Analysis. 2nd ed. Cambridge University Press; 2008. Figure 1.19. This visualization of the relationships…
This tool is fantastic! I was able to generate a Fourier-Poisson cube [0] in about 10 minutes, and the UI is incredibly intuitive. The focus on commutative diagrams, rather than a free-form canvas, is a brilliant design…
Be careful, the weight of Algorithm A by Efraimidis and Spirakis cannot be interpreted as the inclusion probability, and thus cannot be used in survey sampling to construct the Horvitz–Thompson estimator. See "Remarks…
If the bus arrives on time, the arrival time would be [tau, 2 * tau, ..., N * tau]. One way to simulate "random" arrival time is to draw uniform points in the interval [0, N * tau]. It turns out the inter-arrival time…
Relevance: from the cited paper, the variance of the median estimator is proportional to 1/(n * f^2), where n is the sample size and f is the density at median. Two observations: 1. With sufficiently large n, you can…
Asymptotic properties of quantile estimators are widely studied [1]. The key is to have a sufficiently large sample size. [1] Bahadur, R. R. (1966). A note on quantiles in large samples. Annals of Mathematical…
My takeaway is to avoid mixing the frequentist and Bayesian approaches. Choose one method: either follow the frequentist approach and avoid early data analysis, or use the Bayesian approach to compute posterior…
I'm grateful for leetcode. Despite my background in electrical engineering, where I specialize in statistical signal processing, I never had the opportunity to delve into algorithm or data structure courses during my…
1/ I think you are referring to pushforward measure (https://en.wikipedia.org/wiki/Pushforward_measure): the random variable "pushes" the probability measure to its codomain. 2/ pdf requires a stronger condition: the…
Agree, this is great! I wonder if there're some ML equivalent sites that present topics in a modular way?
Maybe "Probability via Expectation" by Peter Whittle https://link.springer.com/book/10.1007/978-1-4612-0509-8 or "Infinite Dimensional Analysis" by Charalambos Aliprantis and Kim Border…
Just curious what are the deeper optimization topics you were hoping to see in the monograph?
Second this. Richard is a great lecturer. Highly recommend his lecture recordings. His winter 2019 lecture videos and materials can be found here: https://github.com/rmcelreath/statrethinking_winter2019
Unless you water them down like some populate science books, I don't understand how you can teach probability and statistics without calculus?
If I remember correctly the royalty was $7.5 per iPhone. Not sure how that alone contributes to the $150 price hike.
Or C-x * for calc-dispatch? I guess the point of this app is the input doesn't have to be precise. Not sure emacs can do that.
Yes but not directly. It is used in the Monte Carlo simulation part. In communication systems everything is complex :D
Last week I converted a simple side project in Python to Julia. It's a sequential Bayeisan estimation problem. A pleasant surprise that the Julia version runs 30x faster than the Python counter part. I am sure the…
Fascinating! Such a great demonstration of Julia's strength. I wish more academic papers are written in this fashion or include a tutorial-like/reproducible post like this.