Regression bei Wachstums- und Zerfallsfunktionen

Regression bei Wachstum- bzw. Zerfallsfunktionen
Statt die Funktionsgleichung über das Lösen des Gleichungssystems zu finden, kann man auch eine Regression durchführen. Dafür darf es sogar mehr als zwei Punkte geben. Dies ist wohl die in der wissenschaftlichen Praxis am häufigsten praktizierte Methode. Denn in der Regel liegen zuerst statistische Daten vor und damit wird dann ein mathematisches Modell entworfen - also eine Funktionsgleichung gesucht.[br][br]Gehen Sie mit dem [b]HP-Prime[/b] folgendermaßen vor:[br][br][list=1][*]Stellen Sie im Rechner die App "[color=#0000ff]Statistiken 2 Var[/color]" ein[/*][*]Sie sind nun im [color=#0000ff]Numerischen Modus[/color] des Rechners (Falls Sie jetzt keine Tabelle sehen, drücken Sie auf die [color=#0000ff][Num][/color]-Taste). Es erscheint eine Tabelle. Geben Sie hier in die ersten beiden Spalten [b]C1[/b] und [b]C2[/b] die [math]x[/math]- und [math]y[/math]-Koordinaten ihrer Messwerte ein.[/*][*]Drücken Sie auf die [color=#0000ff][Symb][/color]-Taste. [/*][*]Tragen Sie in das erste Textfeld oben links den Namen der Spalte ein, in der die Koordinaten für die Abszisse stehen (das ist häufig C1)[/*][*]Tragen Sie in das zweite Textfeld den Namen der Spalte ein, in der die Funktionswerte - also die y-Koordinaten - stehen (das ist häufig C2). 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[/img] 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[/img][br][br]Wecheln Sie nun mit [Symb] in die Symbolische 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[/img][br][br][color=#980000]Bis hier hin verläuft es bei allen Wachstums- und Zerfallsvorgängen gleich. Aber ab hier muss zwischen den Wachstumsarten unterschieden werden:[/color][/i][/b]
Lineare Regression mit dem HP Prime
[list][*]Als erstes muss für eine lineare Regression der [b]Regressionstyp[/b] [color=#0000ff]Linear[/color] eingestellt werden. [/*][*]Drücken sie nun auf das Feld [color=#0000ff]Anpass[/color] auf der Menüzeile am unteren Rand des Displays, so dass daneben ein [color=#0000ff]Punkt[/color] zu sehen ist.Wenn dieser Punkt nicht zusehen ist, dann sieht man in der grafischen Darstellung nur die Punkte, aber nichtden Funktionsgraphen der Regressionsfunktion.[/*][*]Nun kann mit den Tasten [color=#0000ff][Shift][/color] und [color=#0000ff][plot][/color] ein sinnvoller Definitions- und Wertebereich für die gesuchte Funktion eingestellt werden.[/*][*]Wenn danach auf [color=#0000ff][plot][/color] gedrückt wird, kann man die Punkte und den Funktionsgraphen der Regressionsfunktion sehen.[/*][*]Nach erneutem Drücken der [color=#0000ff][Symb][/color]-Taste kann man unter [color=#0000ff]Anpassung[/color] die Funktionsgleichung ablesen.[br][/*][/list][br][br]Die Funktionsgleichung kann mit [color=#0000ff][Shift]+[Copy][/color] kopiert und mit [color=#0000ff][Shift]+[Paste][/color] in das CAS-Fenster übertragen werden, um die Funktionsgleichung abzuspeichern und bei Bedarf weitere Rechnungen damit durchzuführen.[br][br][size=150][b][color=#980000]Aber Achtung:[/color][/b][/size] In der Symbolischen Ansicht wird als Variable ein [b]großes X[/b] verwendet, während im CAS-Fenster das [b]kleine x[/b] die Variable ist. Sie müssen in der hineinkopierten Gleichung erst [b]alle großen X durch kleine x ersetzen[/b], und die Funktion [b][color=#980000]dann erst[/color][/b] als z.B. [math]f(x)[/math] abspeichern.[br]
Exponentielle Regression mit dem HP Prime
Hier ist das Verfahren das gleiche, wie bei der linearen Regression, nur dass bei [b]Regressionstyp[/b] "[color=#980000]Exponentiell[/color]" eingetragen werden muss.[br][br][b][color=#980000]Achtung:[/color][/b] Wenn unter den Messwerten negative y-Werte sind, dann streiken die Computer-Algebra-Systeme wie Geogebra oder der HP-Prime. Denn diese Systeme wissen, dass eine Exponentialfunktion niemals einen negativen Wert annehmen kann.
Logistische Regression mit dem HP Prime
Hier ist das Verfahren das gleiche, wie bei der linearen Regression, nur dass bei [b]Regressionstyp[/b] "[color=#980000]Logistisch[/color]" eingetragen werden muss.
Regression bei beschränktem Zerfall mit dem HP Prime
Um eine Regression bei beschränktem Zerfall durchzuführen, muss man den Wert der unteren Grenze [math]G[/math] kennen, den die Funktionswerte nicht unterschreiten können. Hier ist es wichtig, dass es wirklich keine y-Koordinate unter den Messwerten gibt, der unterhalb dieser Grenze [math]G[/math] liegt. Das würde zu einer Fehlermeldung führen[br][list][*]Verbessern Sie in der Symbolischen Ansicht (Taste [Symb]) das zweite Textfeld, in dem der Name der Spalte für die y-Koordinaten steht, indem Sie hinter den Namen der Spalte ein [math]-G[/math] einsetzen (also zum Beispiel [b]C2-G[/b]), wobei sie für das [math]G[/math] den Zahlenwert der unteren Grenze einfügen.[/*][*]Wählen Sie als [b]Regressionstyp[/b] nun "[color=#980000]Exponentiell[/color]".[/*][*]Drücken Sie auf [Anpass] und wecheln Sie kurz mit [plot] in den grafischen Modus des Rechners, um gleich mit [Symb] wieder in die Symbolische Ansicht zurückzukehren. Hier können Sie nun unter "Anpassung" einen Funktionsterm ablesen. [/*][*][color=#980000]Dieser Funktionsterm muss nun aber noch korrigiert werden[/color]. Kopieren Sie diesen Term mit [Shift]+[Copy] und  [Shift]+[Paste] in das CAS-Fenster und [b]addieren Sie die Grenze [/b][math]G[/math] [b]zu diesem Term[/b]. Die so korrigierte Funktionsgleichung ist die gesuchte Funktionsgleichung für den beschränkten Zerfall. Speichern Sie diese ab für weitere Rechnungen.[br][/*][/list][b][color=#980000]Achtung:[/color][/b] Wenn es unter den Messwerten welche gibt, die kleiner als die untere Grenze sind, dann wird keine Funktion gefunden, weil die Computer-Algebra-Systeme (CAS) davon ausgehen, dass dies nicht möglich ist.
Regression bei beschränktem Wachstum mit dem HP Prime
Um eine Regression bei beschränktem Wachstum durchzuführen, muss man den Wert der oberen Grenze [math]G[/math] kennen, den die Funktionswerte nicht erreichen können. Hier ist es wichtig, dass es wirklich keine y-Koordinate unter den Messwerten gibt, der über dieser Grenze [math]G[/math] liegt. Das würde zu einer Fehlermeldung führen[br][list][*]Verbessern Sie in der Symbolischen Ansicht (Taste [Symb]) das zweite Textfeld, in dem der Name der Spalte für die y-Koordinaten steht, indem Sie vor den Namen der Spalte ein [math]G-[/math] einsetzen (also zum Beispiel [b]G-C2[/b]), wobei sie für das [math]G[/math] den Zahlenwert der unteren Grenze einfügen.[/*][*]Wählen Sie als [b]Regressionstyp[/b] nun "[color=#980000]Exponentiell[/color]".[/*][*]Drücken Sie auf [Anpass] und wecheln Sie kurz mit [plot] in den grafischen Modus des Rechners, um gleich mit [Symb] wieder in die Symbolische Ansicht zurückzukehren. Hier können Sie nun unter "Anpassung" einen Funktionsterm ablesen. [/*][*][color=#980000]Dieser Funktionsterm muss nun aber noch korrigiert werden[/color]. Kopieren Sie diesen Term mit [Shift]+[Copy] und  [Shift]+[Paste] in das CAS-Fenster und [b]ziehen Sie diesen Funktionsterm von der Grenze [/b][math]G[/math] [b]ab [/b](also [math]G-...[/math]). Die so korrigierte Funktionsgleichung ist die gesuchte Funktionsgleichung für das beschränkte Wachstum. Speichern Sie diese ab für weitere Rechnungen.[br][/*][/list][b][color=#980000]Achtung:[/color][/b] Wenn es unter den Messwerten welche gibt, die größer als die obere Grenze sind, dann wird keine Funktion gefunden, weil die Computer-Algebra-Systeme (CAS) davon ausgehen, dass dies nicht möglich ist.
Regression bei logistischem Wachstum
Hier ist das Verfahren das gleiche, wie bei der linearen Regression, nur dass bei [b]Regressionstyp[/b] "[color=#980000]logistisch[/color]" eingetragen werden muss.[br][br][b][color=#980000]Achtung:[/color][/b] Wenn unter den Messwerten y-Werte sind, die negativ sind, dann streiken die Computer-Algebra-Systeme wie Geogebra oder der HP-Prime. Denn diese Systeme wissen, dass eine Exponentialfunktion niemals einen negativen Wert annehmen kann.

Information: Regression bei Wachstums- und Zerfallsfunktionen