RollingFunctions.jl

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Feature request: TimeArrays support

3

It would be nnatural to run rolling functions on (multidimensional) time-series (TimeArrays in Julia) and get TimeArray back. Thanks in advance.

StepanSushko

Rolling does not respect type, converts to float

3

Function rolling returns float for int arguments, it should keep the type and not make conversions unless the aggregation function needs it. See ```julia julia> data = 1:5 1:5 julia>...

racinmat

rollsum, runsum

1

Thanks for this package! I kindly request rollsum and runsum functions. And more documentation on the custom functions running(function, data, windowsize).

Mastomaki

rolling regression

9

Could you add a rolling regression function that can return the regression coefficients and R squared value? With this function, your package would be super useful for time series analysis.

waynelapierre

Compatibility with CUDA ?

1

Currently rolling functions return an array on the cpu no matter the type of the input array. This means that the result must be moved back to the gpu after...

HenriDeh

Rolling Regression?

3

Hello, thank you for your commitment. I want to know if RollingFunctions can be implemented when I have more than one variable. Especially I want to use it to calculate...

SeongDeokKo

Just a notification about package offering some similar functionality: https://github.com/sairus7/MaxMinFilters.jl And a discourse about possible generalization of DSP-related packages: https://discourse.julialang.org/t/ann-maxminfilters-jl-fast-streaming-maximum-minimum-within-moving-window/30151

sairus7

Unused type parameters

1

Julia 1.9 shows these warnings when testing the package. The redundant type parameters can just be removed. ``` WARNING: method definition for rolling at /home/pkgeval/.julia/packages/RollingFunctions/4Jh9c/src/roll/rolling.jl:44 declares type variable N but...

KristofferC

Add support for padding with sentinel value for roll*

57

Example: ``` julia> rollmean(1:5, 3) 3-element Vector{Float64}: 2.0 3.0 4.0 julia> runmean(1:5, 3) 5-element Vector{Float64}: 1.0 1.5 2.0 3.0 4.0 julia> [fill(missing, 2); rollmean(1:5, 3)] 5-element Vector{Union{Missing, Float64}}: missing missing...

bkamins

Feature request: rolling(function, data, windowsize, stride)

1

rolling(function, data, windowsize, stride) stride is step length of roll window

zsz00