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CHANGELOG

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Changes in SysIdentPy
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=====================
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v0.3.2
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------
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CONTRIBUTORS
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~~~~~~~~~~~~
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- wilsonrljr
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CHANGES
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~~~~~~~
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- The update **v0.3.2** has been released with API changes and fixes.
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- Major:
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- Added Akaike Information Criteria corrected in FROLS. Now the user can use aicc as the information criteria to select the model order when using FROLS algorithm.
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- FIX: Issue #114. Replace yhat with y in root relative squared error. Thanks @miroder
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- TESTS: Minor changes in tests by removing unnecessary data load.
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- Remove unused code and comments.
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- Docs: Minor changes in notebooks. Added AICc method in the information criteria example.
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v0.3.1
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docs/book/contents/index.html

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<!DOCTYPE html>
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<html class="no-js" lang="en"> <head><meta charset="utf-8"/><meta content="width=device-width,initial-scale=1" name="viewport"/><meta content="From Classical Approaches to Neural Networks" name="description"/><meta content="Wilson Rocha" name="author"/><link href="https://sysidentpy.org/book/contents/" rel="canonical"/><link href="../preface/" rel="prev"/><link href="../../events/events/" rel="next"/><link href="../../overrides/assets/images/favicon.png" rel="icon"/><meta content="mkdocs-1.4.3, mkdocs-material-9.1.11" name="generator"/><title>Contents - SysIdentPy</title><link href="../../assets/stylesheets/main.85bb2934.min.css" rel="stylesheet"/><link href="../../assets/stylesheets/palette.a6bdf11c.min.css" rel="stylesheet"/><link crossorigin="" href="https://fonts.gstatic.com" rel="preconnect"/><link href="https://fonts.googleapis.com/css?family=Roboto:300,300i,400,400i,700,700i%7CRoboto+Mono:400,400i,700,700i&amp;display=fallback" rel="stylesheet"/><style>:root{--md-text-font:"Roboto";--md-code-font:"Roboto Mono"}</style><link href="../../assets/_mkdocstrings.css" rel="stylesheet"/><script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script><script id="__analytics">function __md_analytics(){function n(){dataLayer.push(arguments)}window.dataLayer=window.dataLayer||[],n("js",new Date),n("config","G-16K3SQT164"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){this.value&&n("event","search",{search_term:this.value})}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");n("event","feedback",{page:t,data:e}),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){n("config","G-16K3SQT164",{page_path:e.pathname})})});var e=document.createElement("script");e.async=!0,e.src="https://www.googletagmanager.com/gtag/js?id=G-16K3SQT164",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script><script>"undefined"!=typeof __md_analytics&&__md_analytics()</script><link href="../../assets/stylesheets/glightbox.min.css" rel="stylesheet"/><style>
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<html class="no-js" lang="en"> <head><meta charset="utf-8"/><meta content="width=device-width,initial-scale=1" name="viewport"/><meta content="From Classical Approaches to Neural Networks" name="description"/><meta content="Wilson Rocha" name="author"/><link href="https://sysidentpy.org/book/contents/" rel="canonical"/><link href="../preface/" rel="prev"/><link href="../../events/events/" rel="next"/><link href="../../overrides/assets/images/favicon.png" rel="icon"/><meta content="mkdocs-1.4.3, mkdocs-material-9.1.11" name="generator"/><title>Contents - SysIdentPy</title><link href="../../assets/stylesheets/main.85bb2934.min.css" rel="stylesheet"/><link href="../../assets/stylesheets/palette.a6bdf11c.min.css" rel="stylesheet"/><link crossorigin="" href="https://fonts.gstatic.com" rel="preconnect"/><link href="https://fonts.googleapis.com/css?family=Roboto:300,300i,400,400i,700,700i%7CRoboto+Mono:400,400i,700,700i&amp;display=fallback" rel="stylesheet"/><style>:root{--md-text-font:"Roboto";--md-code-font:"Roboto Mono"}</style><link href="../../assets/_mkdocstrings.css" rel="stylesheet"/><script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script><script>"undefined"!=typeof __md_analytics&&__md_analytics()</script><link href="../../assets/stylesheets/glightbox.min.css" rel="stylesheet"/><style>
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docs/book/preface/index.html

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<!DOCTYPE html>
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<html class="no-js" lang="en"> <head><meta charset="utf-8"/><meta content="width=device-width,initial-scale=1" name="viewport"/><meta content="From Classical Approaches to Neural Networks" name="description"/><meta content="Wilson Rocha" name="author"/><link href="https://sysidentpy.org/book/preface/" rel="canonical"/><link href="../../examples/PV_forecasting_benchmark/" rel="prev"/><link href="../contents/" rel="next"/><link href="../../overrides/assets/images/favicon.png" rel="icon"/><meta content="mkdocs-1.4.3, mkdocs-material-9.1.11" name="generator"/><title>Preface - SysIdentPy</title><link href="../../assets/stylesheets/main.85bb2934.min.css" rel="stylesheet"/><link href="../../assets/stylesheets/palette.a6bdf11c.min.css" rel="stylesheet"/><link crossorigin="" href="https://fonts.gstatic.com" rel="preconnect"/><link href="https://fonts.googleapis.com/css?family=Roboto:300,300i,400,400i,700,700i%7CRoboto+Mono:400,400i,700,700i&amp;display=fallback" rel="stylesheet"/><style>:root{--md-text-font:"Roboto";--md-code-font:"Roboto Mono"}</style><link href="../../assets/_mkdocstrings.css" rel="stylesheet"/><script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script><script id="__analytics">function __md_analytics(){function n(){dataLayer.push(arguments)}window.dataLayer=window.dataLayer||[],n("js",new Date),n("config","G-16K3SQT164"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){this.value&&n("event","search",{search_term:this.value})}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");n("event","feedback",{page:t,data:e}),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){n("config","G-16K3SQT164",{page_path:e.pathname})})});var e=document.createElement("script");e.async=!0,e.src="https://www.googletagmanager.com/gtag/js?id=G-16K3SQT164",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script><script>"undefined"!=typeof __md_analytics&&__md_analytics()</script><link href="../../assets/stylesheets/glightbox.min.css" rel="stylesheet"/><style>
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<html class="no-js" lang="en"> <head><meta charset="utf-8"/><meta content="width=device-width,initial-scale=1" name="viewport"/><meta content="From Classical Approaches to Neural Networks" name="description"/><meta content="Wilson Rocha" name="author"/><link href="https://sysidentpy.org/book/preface/" rel="canonical"/><link href="../../examples/PV_forecasting_benchmark/" rel="prev"/><link href="../contents/" rel="next"/><link href="../../overrides/assets/images/favicon.png" rel="icon"/><meta content="mkdocs-1.4.3, mkdocs-material-9.1.11" name="generator"/><title>Preface - SysIdentPy</title><link href="../../assets/stylesheets/main.85bb2934.min.css" rel="stylesheet"/><link href="../../assets/stylesheets/palette.a6bdf11c.min.css" rel="stylesheet"/><link crossorigin="" href="https://fonts.gstatic.com" rel="preconnect"/><link href="https://fonts.googleapis.com/css?family=Roboto:300,300i,400,400i,700,700i%7CRoboto+Mono:400,400i,700,700i&amp;display=fallback" rel="stylesheet"/><style>:root{--md-text-font:"Roboto";--md-code-font:"Roboto Mono"}</style><link href="../../assets/_mkdocstrings.css" rel="stylesheet"/><script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script><script>"undefined"!=typeof __md_analytics&&__md_analytics()</script><link href="../../assets/stylesheets/glightbox.min.css" rel="stylesheet"/><style>
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html.glightbox-open { overflow: initial; height: 100%; }
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.gslide-title { margin-top: 0px; user-select: text; }
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docs/changelog/changelog.md

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# Changes in SysIdentPy
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## v0.3.2
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### CONTRIBUTORS
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- wilsonrljr
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### CHANGES
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- The update **v0.3.2** has been released with API changes and fixes.
17+
18+
- Major:
19+
- Added Akaike Information Criteria corrected in FROLS. Now the user can use aicc as the information criteria to select the model order when using FROLS algorithm.
20+
21+
- FIX: Issue #114. Replace yhat with y in root relative squared error. Thanks @miroder
22+
23+
- TESTS: Minor changes in tests by removing unnecessary data load.
24+
25+
- Remove unused code and comments.
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- Docs: Minor changes in notebooks. Added AICc method in the information criteria example.
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## v0.3.1
930

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### CONTRIBUTORS

docs/changelog/changelog/changelog.md

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# Changes in SysIdentPy
77

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## v0.3.2
9+
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### CONTRIBUTORS
11+
12+
- wilsonrljr
13+
14+
### CHANGES
15+
16+
- The update **v0.3.2** has been released with API changes and fixes.
17+
18+
- Major:
19+
- Added Akaike Information Criteria corrected in FROLS. Now the user can use aicc as the information criteria to select the model order when using FROLS algorithm.
20+
21+
- FIX: Issue #114. Replace yhat with y in root relative squared error. Thanks @miroder
22+
23+
- TESTS: Minor changes in tests by removing unnecessary data load.
24+
25+
- Remove unused code and comments.
26+
27+
- Docs: Minor changes in notebooks. Added AICc method in the information criteria example.
28+
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## v0.3.1
930

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### CONTRIBUTORS

docs/changelog/changelog/index.html

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docs/code/aols/index.html

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<html class="no-js" lang="en"> <head><meta charset="utf-8"/><meta content="width=device-width,initial-scale=1" name="viewport"/><meta content="From Classical Approaches to Neural Networks" name="description"/><meta content="Wilson Rocha" name="author"/><link href="https://sysidentpy.org/code/aols/" rel="canonical"/><link href="../metamss/" rel="prev"/><link href="../entropic-regression/" rel="next"/><link href="../../overrides/assets/images/favicon.png" rel="icon"/><meta content="mkdocs-1.4.3, mkdocs-material-9.1.11" name="generator"/><title>AOLS - SysIdentPy</title><link href="../../assets/stylesheets/main.85bb2934.min.css" rel="stylesheet"/><link href="../../assets/stylesheets/palette.a6bdf11c.min.css" rel="stylesheet"/><link crossorigin="" href="https://fonts.gstatic.com" rel="preconnect"/><link href="https://fonts.googleapis.com/css?family=Roboto:300,300i,400,400i,700,700i%7CRoboto+Mono:400,400i,700,700i&amp;display=fallback" rel="stylesheet"/><style>:root{--md-text-font:"Roboto";--md-code-font:"Roboto Mono"}</style><link href="../../assets/_mkdocstrings.css" rel="stylesheet"/><script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script><script id="__analytics">function __md_analytics(){function n(){dataLayer.push(arguments)}window.dataLayer=window.dataLayer||[],n("js",new Date),n("config","G-16K3SQT164"),document.addEventListener("DOMContentLoaded",function(){document.forms.search&&document.forms.search.query.addEventListener("blur",function(){this.value&&n("event","search",{search_term:this.value})}),document$.subscribe(function(){var a=document.forms.feedback;if(void 0!==a)for(var e of a.querySelectorAll("[type=submit]"))e.addEventListener("click",function(e){e.preventDefault();var t=document.location.pathname,e=this.getAttribute("data-md-value");n("event","feedback",{page:t,data:e}),a.firstElementChild.disabled=!0;e=a.querySelector(".md-feedback__note [data-md-value='"+e+"']");e&&(e.hidden=!1)}),a.hidden=!1}),location$.subscribe(function(e){n("config","G-16K3SQT164",{page_path:e.pathname})})});var e=document.createElement("script");e.async=!0,e.src="https://www.googletagmanager.com/gtag/js?id=G-16K3SQT164",document.getElementById("__analytics").insertAdjacentElement("afterEnd",e)}</script><script>"undefined"!=typeof __md_analytics&&__md_analytics()</script><link href="../../assets/stylesheets/glightbox.min.css" rel="stylesheet"/><style>
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<html class="no-js" lang="en"> <head><meta charset="utf-8"/><meta content="width=device-width,initial-scale=1" name="viewport"/><meta content="From Classical Approaches to Neural Networks" name="description"/><meta content="Wilson Rocha" name="author"/><link href="https://sysidentpy.org/code/aols/" rel="canonical"/><link href="../metamss/" rel="prev"/><link href="../entropic-regression/" rel="next"/><link href="../../overrides/assets/images/favicon.png" rel="icon"/><meta content="mkdocs-1.4.3, mkdocs-material-9.1.11" name="generator"/><title>AOLS - SysIdentPy</title><link href="../../assets/stylesheets/main.85bb2934.min.css" rel="stylesheet"/><link href="../../assets/stylesheets/palette.a6bdf11c.min.css" rel="stylesheet"/><link crossorigin="" href="https://fonts.gstatic.com" rel="preconnect"/><link href="https://fonts.googleapis.com/css?family=Roboto:300,300i,400,400i,700,700i%7CRoboto+Mono:400,400i,700,700i&amp;display=fallback" rel="stylesheet"/><style>:root{--md-text-font:"Roboto";--md-code-font:"Roboto Mono"}</style><link href="../../assets/_mkdocstrings.css" rel="stylesheet"/><script>__md_scope=new URL("../..",location),__md_hash=e=>[...e].reduce((e,_)=>(e<<5)-e+_.charCodeAt(0),0),__md_get=(e,_=localStorage,t=__md_scope)=>JSON.parse(_.getItem(t.pathname+"."+e)),__md_set=(e,_,t=localStorage,a=__md_scope)=>{try{t.setItem(a.pathname+"."+e,JSON.stringify(_))}catch(e){}}</script><script>"undefined"!=typeof __md_analytics&&__md_analytics()</script><link href="../../assets/stylesheets/glightbox.min.css" rel="stylesheet"/><style>
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docs/code/basis-function/index.html

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