#longmemory — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #longmemory, aggregated by home.social.
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An actor can remember his briefest notice well into senescence and long after he has forgotten his phone number and where he lives.
Jean Kerr (1922-2003) American author and playwright [b. Bridget Jean Collins]
Essay (1957), “One Half of Two on the Aisle,” Please Don’t Eat the DaisiesMore about this quote: wist.info/kerr-jean/83220/
#quote #quotes #quotation #qotd #jeankerr #actor #ego #longmemory #memory #memoryloss #review
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An actor can remember his briefest notice well into senescence and long after he has forgotten his phone number and where he lives.
Jean Kerr (1922-2003) American author and playwright [b. Bridget Jean Collins]
Essay (1957), “One Half of Two on the Aisle,” Please Don’t Eat the DaisiesMore about this quote: wist.info/kerr-jean/83220/
#quote #quotes #quotation #qotd #jeankerr #actor #ego #longmemory #memory #memoryloss #review
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An actor can remember his briefest notice well into senescence and long after he has forgotten his phone number and where he lives.
Jean Kerr (1922-2003) American author and playwright [b. Bridget Jean Collins]
Essay (1957), “One Half of Two on the Aisle,” Please Don’t Eat the DaisiesMore about this quote: wist.info/kerr-jean/83220/
#quote #quotes #quotation #qotd #jeankerr #actor #ego #longmemory #memory #memoryloss #review
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An actor can remember his briefest notice well into senescence and long after he has forgotten his phone number and where he lives.
Jean Kerr (1922-2003) American author and playwright [b. Bridget Jean Collins]
Essay (1957), “One Half of Two on the Aisle,” Please Don’t Eat the DaisiesMore about this quote: wist.info/kerr-jean/83220/
#quote #quotes #quotation #qotd #jeankerr #actor #ego #longmemory #memory #memoryloss #review
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An actor can remember his briefest notice well into senescence and long after he has forgotten his phone number and where he lives.
Jean Kerr (1922-2003) American author and playwright [b. Bridget Jean Collins]
Essay (1957), “One Half of Two on the Aisle,” Please Don’t Eat the DaisiesMore about this quote: wist.info/kerr-jean/83220/
#quote #quotes #quotation #qotd #jeankerr #actor #ego #longmemory #memory #memoryloss #review
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Bovino not welcome in Vegas
“Upon becoming aware of the individual’s presence, the patron was asked to leave the premises and was escorted out by staff in accordance with venue policy to maintain a safe and orderly environment for all patrons,” the venue said...Bottled Blonde did not provide further details other than describing itself as a private business that “does not engage in political activity or affiliations” and “reserves the right to refuse service to any patron at its discretion.”
#nazis #usPol #shunTheCunts #longMemory
https://lasvegassun.com/news/2026/feb/05/border-patrol-boss-gregory-bovino-tossed-from-las/
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Ved slutningen af mit disputatsforsvar i 2005 blev jeg spurgt, hvad mit næste Grundtvigprojekt skulle være. Spørgsmålet tog mig på sengen - blandt andet fordi jeg endnu ingen planer havde om et Grundtvigprojekt - så jeg svarede så godt som i blinde og lidt drillende, at jeg gerne ville skrive en bog om "Grundtvig som fugl".
Prøv at gætte, hvilket billede der maser sig på, når man skriver om Grundtvigs salmer.
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In connection with #juliacon2024 (which I sadly could not attend), LongMemory.jl has been updated to v0.1.2. The main addition to the package is the test for change in persistence. It is now possible to test if the long memory parameter changed (decreased or increased) in a given sample. The function uses the fast Fourier transform to speed up computations. https://everval.github.io/LongMemory.jl/dev/#Structural-Changes #julialang #timeseries #longmemory #timeseriesanalysis
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I'm happy to announce that the accompanying manuscript 📜 to LongMemory.jl is now available in arXiv 📰
The paper describes the theoretical developments behind the (many) functions available in the package and illustrates them using the Nile River dataset also included in the package 🌊 Replication notebooks for all the figures and results in the manuscript are available at the package's and my personal website 👩💻
I welcome suggestions on how to improve the package and the paper. #JuliaLang #programming #timeseries #statisticalsoftware #longmemory https://arxiv.org/abs/2401.14077 -
Introducing LongMemory.jl: A Julia Package for Long Memory Time Series Analysis 🖥️📚📈📊
I am happy to announce that after several months of getting to understand the language better, I have finally published my first Julia registered package: LongMemory.jl. 🙂 This package is the result of my research on long memory time series analysis, which is a fascinating topic in econometrics and statistics. Long memory models are useful for capturing the persistence and dependence of many real-world phenomena, such as inflation, interest rates, volatility, network traffic, and environmental data.
LongMemory.jl makes it easy to generate, estimate, and forecast long memory models in Julia. It supports various types of models, such as fractional differencing, cross-sectional aggregation, and stochastic duration shocks. It also provides functions for testing the presence of long memory, computing the Hurst exponent, and simulating long memory processes. The package is fully documented and includes classical data examples, such as the Nile River minima. 🌊
The package can be installed easily from the Julia general registry. I have prepared a short video that shows how to install the package and generate long memory diagnostics plots for the Nile River minima dataset. The Nile River minima is a famous example of a long memory time series.
I hope you find LongMemory.jl useful and practical. I welcome any feedback, suggestions, or contributions to improve the package. You can contact me or open an issue on GitHub. Thank you for your interest and feedback!
#julialang #programming #programmingjourney #longmemory #timeseriesanalysis #timeseries #econometrics #statistics @[email protected] @[email protected]
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Introducing LongMemory.jl: A Julia Package for Long Memory Time Series Analysis 🖥️📚📈📊
I am happy to announce that after several months of getting to understand the language better, I have finally published my first Julia registered package: LongMemory.jl. 🙂 This package is the result of my research on long memory time series analysis, which is a fascinating topic in econometrics and statistics. Long memory models are useful for capturing the persistence and dependence of many real-world phenomena, such as inflation, interest rates, volatility, network traffic, and environmental data.
LongMemory.jl makes it easy to generate, estimate, and forecast long memory models in Julia. It supports various types of models, such as fractional differencing, cross-sectional aggregation, and stochastic duration shocks. It also provides functions for testing the presence of long memory, computing the Hurst exponent, and simulating long memory processes. The package is fully documented and includes classical data examples, such as the Nile River minima. 🌊
The package can be installed easily from the Julia general registry. I have prepared a short video that shows how to install the package and generate long memory diagnostics plots for the Nile River minima dataset. The Nile River minima is a famous example of a long memory time series.
I hope you find LongMemory.jl useful and practical. I welcome any feedback, suggestions, or contributions to improve the package. You can contact me or open an issue on GitHub. Thank you for your interest and feedback!
#julialang #programming #programmingjourney #longmemory #timeseriesanalysis #timeseries #econometrics #statistics @[email protected] @[email protected]
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Introducing LongMemory.jl: A Julia Package for Long Memory Time Series Analysis 🖥️📚📈📊
I am happy to announce that after several months of getting to understand the language better, I have finally published my first Julia registered package: LongMemory.jl. 🙂 This package is the result of my research on long memory time series analysis, which is a fascinating topic in econometrics and statistics. Long memory models are useful for capturing the persistence and dependence of many real-world phenomena, such as inflation, interest rates, volatility, network traffic, and environmental data.
LongMemory.jl makes it easy to generate, estimate, and forecast long memory models in Julia. It supports various types of models, such as fractional differencing, cross-sectional aggregation, and stochastic duration shocks. It also provides functions for testing the presence of long memory, computing the Hurst exponent, and simulating long memory processes. The package is fully documented and includes classical data examples, such as the Nile River minima. 🌊
The package can be installed easily from the Julia general registry. I have prepared a short video that shows how to install the package and generate long memory diagnostics plots for the Nile River minima dataset. The Nile River minima is a famous example of a long memory time series.
I hope you find LongMemory.jl useful and practical. I welcome any feedback, suggestions, or contributions to improve the package. You can contact me or open an issue on GitHub. Thank you for your interest and feedback!
#julialang #programming #programmingjourney #longmemory #timeseriesanalysis #timeseries #econometrics #statistics @[email protected] @[email protected]
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Introducing LongMemory.jl: A Julia Package for Long Memory Time Series Analysis 🖥️📚📈📊
I am happy to announce that after several months of getting to understand the language better, I have finally published my first Julia registered package: LongMemory.jl. 🙂 This package is the result of my research on long memory time series analysis, which is a fascinating topic in econometrics and statistics. Long memory models are useful for capturing the persistence and dependence of many real-world phenomena, such as inflation, interest rates, volatility, network traffic, and environmental data.
LongMemory.jl makes it easy to generate, estimate, and forecast long memory models in Julia. It supports various types of models, such as fractional differencing, cross-sectional aggregation, and stochastic duration shocks. It also provides functions for testing the presence of long memory, computing the Hurst exponent, and simulating long memory processes. The package is fully documented and includes classical data examples, such as the Nile River minima. 🌊
The package can be installed easily from the Julia general registry. I have prepared a short video that shows how to install the package and generate long memory diagnostics plots for the Nile River minima dataset. The Nile River minima is a famous example of a long memory time series.
I hope you find LongMemory.jl useful and practical. I welcome any feedback, suggestions, or contributions to improve the package. You can contact me or open an issue on GitHub. Thank you for your interest and feedback!
#julialang #programming #programmingjourney #longmemory #timeseriesanalysis #timeseries #econometrics #statistics @[email protected] @[email protected]
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Introducing LongMemory.jl: A Julia Package for Long Memory Time Series Analysis 🖥️📚📈📊
I am happy to announce that after several months of getting to understand the language better, I have finally published my first Julia registered package: LongMemory.jl. 🙂 This package is the result of my research on long memory time series analysis, which is a fascinating topic in econometrics and statistics. Long memory models are useful for capturing the persistence and dependence of many real-world phenomena, such as inflation, interest rates, volatility, network traffic, and environmental data.
LongMemory.jl makes it easy to generate, estimate, and forecast long memory models in Julia. It supports various types of models, such as fractional differencing, cross-sectional aggregation, and stochastic duration shocks. It also provides functions for testing the presence of long memory, computing the Hurst exponent, and simulating long memory processes. The package is fully documented and includes classical data examples, such as the Nile River minima. 🌊
The package can be installed easily from the Julia general registry. I have prepared a short video that shows how to install the package and generate long memory diagnostics plots for the Nile River minima dataset. The Nile River minima is a famous example of a long memory time series.
I hope you find LongMemory.jl useful and practical. I welcome any feedback, suggestions, or contributions to improve the package. You can contact me or open an issue on GitHub. Thank you for your interest and feedback!
#julialang #programming #programmingjourney #longmemory #timeseriesanalysis #timeseries #econometrics #statistics @[email protected] @[email protected]