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MMQ para fun\[CCedilla]\[OTilde]es n\[ATilde]o-lineares em apenas 1 ou 2 par\
\[AHat]metros e lineares nos demais\
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Note que a principal mudan\[CCedilla]a por usar os pesos corretos \
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Criar uma fun\[CCedilla]\[ATilde]o que ajusta e devolve s\[OAcute] os par\
\[AHat]metros ajustados\
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Aten\[CCedilla]\[ATilde]o, n\[ATilde]o confundir o par\[AHat]metro da fun\
\[CCedilla]\[ATilde]o simulaFit - \[Omega]0 - com a vari\[AAcute]vel \[Omega] \
da fun\[CCedilla]\[ATilde]o \[Alpha] Sin[\[Omega] t] que entra em \
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\[AGrave]s vezes, o algoritmo de NonlinearModelFit pode n\[ATilde]o encontrar \
o m\[IAcute]nimo com a precis\[ATilde]o estabelecida (quando n\[ATilde]o se \
estabelece um AccuracyGoal, a rotina usa AccuracyGoal=1/2 PrecisionGoal que, \
por default, \[EAcute] MachinePrecision=16 d\[IAcute]gitos. Assim, ele est\
\[AAcute] tentando encontrar os valores com 8 d\[IAcute]gitos de precis\
\[ATilde]o, que pode ser muito. Nesse caso, pode-se mudar simulaFit para \
incluir na chamada de NolinearModelFit a op\[CCedilla]\[ATilde]o AccuracyGoal\
\[Rule]5, por exemplo.\
\>", "Text",
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Neste caso, a tendenciosidade \[EAcute] pequena, muito menor que o \
desvio-padr\[ATilde]o do resultado, e n\[ATilde]o precisa ser corrigida - h\
\[AAcute] algo errado com os n\[UAcute]meros do texto! J\[AAcute] o \
desvio-padr\[ATilde]o estimado merece ser modificado:\
\>", "Text",
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Frequentemente \[EAcute] melhor desenhar a curva de soma dos res\[IAcute]duos \
em fun\[CCedilla]\[ATilde]o do par\[AHat]metro n\[ATilde]o-linear\
\>", "Subsection",
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primeiro, um exemplo no caso de um \[UAcute]nico par\[AHat]metro \
n\[ATilde]o-linear\
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mude a incerteza e a fra\[CCedilla]\[ATilde]o do per\[IAcute]odo e veja como \
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\[EAcute] muito comum graficar-se o res\[IAcute]duo normalizado pelos \
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