++ 3dNLfim: AFNI version=AFNI_2011_12_21_1014 (Dec 16 2015) [64-bit] ++ Authored by: B. Douglas Ward This program calculates a nonlinear regression for each voxel of the input AFNI 3d+time data set. The nonlinear regression is calculated by means of a least squares fit to the signal plus noise models which are specified by the user.
Usage: 3dNLfim
-input fname fname = filename of 3d + time data file for input
time series for regresion analysis; default = 0
[The default is to compute with delt = 1.0 ] [The model functions are calculated using a
time grid of: 0, delt, 2*delt, 3*delt, ... ]
-signal slabel slabel = name of (non-linear) signal model
-noise nlabel nlabel = name of (linear) noise model
c <= gs[k] <= d
- N.B.: -sconstr and **-nconstr options must appear
- AFTER -signal and -noise on the command line
[-nrand n] n = number of random test points [default=19999]
[-nbest b] b = use b best test points to start [default=9]
[-rmsmin r] r = minimum rms error to reject reduced model
[-voxel_count] display (to screen) the current voxel index
— These options choose the least-square minimization algorithm —
[-SIMPLEX] use Nelder-Mead simplex method [default]
— These options generate individual AFNI 2 sub-brick datasets — — [All these options must be AFTER options -signal and -noise]—
— These options generate one AFNI ‘bucket’ type dataset —
The mth sub-brick will contain: [-brick m scoef k label] kth signal parameter regression coefficient [-brick m ncoef k label] kth noise parameter regression coefficient [-brick m tmax label] time at max. abs. value of signal [-brick m smax label] signed max. value of signal [-brick m psmax label] signed max. value of signal as percent
above baseline level
[-brick m area label] area between signal and baseline [-brick m parea label] signed area between signal and baseline
as percent of baseline area
[-brick m tscoef k label] t-stat for kth signal parameter coefficient [-brick m tncoef k label] t-stat for kth noise parameter coefficient [-brick m resid label] std. dev. of the full model fit residuals [-brick m rsqr label] R^2 (coefficient of multiple determination) [-brick m fstat label] F-stat for significance of the regression
curves into the output dataset. (Same as ‘setenv AFNI_AUTOMATIC_FDR NO’)
— These options write time series fit for — — each voxel to an AFNI 3d+time dataset —
[-sfit fname] fname = prefix for output 3d+time signal model fit
[-snfit fname] fname = prefix for output 3d+time signal+noise fit
- -jobs J Run the program with ‘J’ jobs (sub-processes).
On a multi-CPU machine, this can speed the program up considerably. On a single CPU machine, using this option is silly. J should be a number from 1 up to the number of CPU sharing memory on the system. J=1 is normal (single process) operation. The maximum allowed value of J is 32.
- For more information on parallelizing, see
Use -mask to get more speed; cf. 3dAutomask.
- Null : No Signal
- (no parameters) see model_null.c
- SineWave_AP : Sinusoidal Response
- (amplitude, phase) see model_sinewave_ap.c
- SquareWave_AP : Square Wave Response
- (amplitude, phase) see model_squarewave_ap.c
- TrnglWave_AP : Triangular Wave Response
- (amplitude, phase) see model_trnglwave_ap.c
- SineWave_APF : Sinusoidal Wave Response
- (amplitude, phase, frequency) see model_sinewave_apf.c
- SquareWave_APF : Sinusoidal Wave Response
- (amplitude, phase, frequency) see model_squarewave_apf.c
- TrnglWave_APF : Sinusoidal Wave Response
- (amplitude, phase, frequency) see model_trnglwave_apf.c
- Exp : Exponential Function
- (a,b): a * exp(b * t) see model_exp.c
- DiffExp : Differential-Exponential Drug Response
- (t0, k, alpha1, alpha2) see model_diffexp.c
- GammaVar : Gamma-Variate Function Drug Response
- (t0, k, r, b) see model_gammavar.c
- Beta : Beta Distribution Model
- (t0, tf, k, alpha, beta) see model_beta.c
- ConvGamma2a : Gamma Convolution with 2 Input Time Series
- (t0, r, b) see model_convgamma2a.c
- ConvGamma : Gamma Vairate Response Model
- (t0, amp, r, b) see model_convgamma.c
- ConvDiffGam : Difference of 2 Gamma Variates
(A0, T0, E0, D0, A1, T1, E1, D1) see model_conv_diffgamma.c
- for help : setenv AFNI_MODEL_HELP_CONVDIFFGAM YES
- 3dNLfim -signal ConvDiffGam
- demri_3 : Dynamic (contrast) Enhanced MRI
(K_trans, Ve, k_ep) see model_demri_3.c
- for help : setenv AFNI_MODEL_HELP_DEMRI_3 YES
- 3dNLfim -signal demri_3
- ADC : Diffusion Signal Model
- (So, D) see model_diffusion.c
- michaelis_menton : Michaelis/Menten Concentration Model
- (v, vmax, k12, k21, mag) see model_michaelis_menton.c
- Expr2 : generic (3dcalc-like) expression with
- exactly 2 ‘free’ parameters and using symbol ‘t’ as the time variable; see model_expr2.c for details.
- ConvCosine4 : 4-piece Cosine Convolution Model
(A, C1, C2, M1, M2, M3, M4) see model_conv_cosine4.c
- for help : setenv AFNI_MODEL_HELP_CONV_COSINE4 YES
- 3dNLfim -signal ConvCosine4
- Zero : Zero Noise Model
- (no parameters) see model_zero.c
- Constant : Constant Noise Model
- (constant) see model_constant.c
- Linear : Linear Noise Model
- (constant, linear) see model_linear.c
- Linear+Ort : Linear+Ort Noise Model
- (constant, linear, Ort) see model_linplusort.c
- Quadratic : Quadratic Noise Model
- (constant, linear, quadratic) see model_quadratic.c
++ Compile date = Dec 16 2015