The qpcR Package - NexTag Supports Open Source Initiatives

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2 AICcmchoice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15modlist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16pcrGOF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17pcrbatch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18pcrfit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19pcrimport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20pcropt1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21pcrplot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23pcrpred . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24<strong>qpcR</strong> . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25repform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27reps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28reps2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29reps3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30resVar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31rutledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31sliwin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Index 34AICcAkaike’s second-order Information Criterion for small sample numbersDescriptionCalculates the second-order (corrected) Akaike information criterion for ’drc’ objects. This is amodified version of the original AIC which compensates for bias with small n. As qPCR datausually has n/par < 40 (see original reference), AICc was implemented to correct for this.UsageAICc(object)Argumentsobjectan object of class ’drc’.DetailsExtends the AIC such that AICc = AIC + 2k(k+1)n−k−1, with k = number of parameters + 1, and n =number of observations. For large n, AICc converges to AIC.Value<strong>The</strong> second-order AIC value.
RMSE 3Author(s)Andrej-Nikolai SpiessReferencesSakamoto, Y., Ishiguro, M., and Kitagawa G. (1986). Akaike Information Criterion Statistics. D.Reidel Publishing Company.Hurvich CM & Tsai CL (1989) Regression and Time Series Model Selection in Small SamplesBiometrika 76, 297-307.See AlsoAIC, logLik.Examplesm
Page 1: The qpcR PackageFebruary 16, 2008Ty
Page 5 and 6: calib 5DetailsThe real-time PCR was
Page 7 and 8: confband 7Examples###define dilutio
Page 9 and 10: efficiency 9Examplesm
Page 11 and 12: evidence 11efficiency(m2, type = "m
Page 13 and 14: expfit 13expfitCalculation of PCR e
Page 15 and 16: mchoice 15ValueA list with the foll
Page 17 and 18: pcrGOF 17DetailsValueFor a more det
Page 19 and 20: pcrfit 19DetailsValueThe qPCR raw d
Page 21 and 22: pcropt1 21Argumentsfilesepheaderquo
Page 23 and 24: pcrplot 23pcrplotPlotting PCR data
Page 25 and 26: qpcR 25Usagepcrpred(object, newdata
Page 27 and 28: epform 27confband qPCR data from Ru
Page 29 and 30: eps2 29Examplesdata(reps)### on sin
Page 31 and 32: esVar 31resVarResidual variance of
Page 33 and 34: sliwin 33DetailsValueTo avoid fits
Page 35: INDEX 35mchoice, 15modlist, 16multd

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