Failure Time of System due to the Hot Electron Effect

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1 of System due to the Hot Electron Effect 1 * exresist; 2 option ls=120 ps=75 nocenter nodate; 3 title of System due to the Hot Electron Effect ; 4 * TIME = failure time (hours) of a system due to drift caused by hot electrons; 5 * RESIST = resistance (micro ohms) of a key resistor; 6 7 data CIRCUIT; input RESIST RESIST2=RESIST*RESIST; 8 RESIST3=RESIST*RESIST2; RESIST4=RESIST2*RESIST2; 9 R1=RESIST-9.889; R2=R1*R1; R3=R1*R2; R4=R2*R2; 10 label TIME= RESIST= Resistance RESIST2= Squared Resistance cards; R= Centered Resistance ; proc print; var TIME RESIST r1; 25 proc plot; plot TIME*RESIST; 26 proc reg; model TIME=RESIST RESIST2/r cli clm; 27 output out=out1 r=resid p=pred; 28 label RESID= Residuals PRED= Predicted Values ; proc plot; plot RESID*RESIST/vref=0; 31 proc rank normal=blom; var RESID; ranks QNORM; 32 proc plot; plot RESID*QNORM; 33 label QNORM= Normal Quantiles ; proc reg; model TIME=RESIST; 36 proc reg; model TIME=RESIST RESIST2 RESIST3; 37 proc reg; model time=resist resist2-resist4; proc corr; var resist resist2-resist4; 40 proc corr; var r1-r4; proc reg; model time=r1-r3; 43 proc reg; model time=r1-r4;

2 of System due to the Hot Electron Effect OBS TIME RESIST R

3 of System due to the Hot Electron Effect 2 Plot of TIME*RESIST. Legend: A = 1 obs, B = 2 obs, etc A A A A A A A A A A A A A A A B A A A A A F a i A A l A u r e T A A i m e A A A NOTE: 1 obs had missing values. Resistance 3

4 of System due to the Hot Electron Effect 3 Model: MODEL1 Model Error Root MSE R-square Dep Mean Adj R-sq C.V Variable DF Estimate Error Parameter=0 Prob > T Label INTERCEP Intercept RESIST Resistance RESIST Squared Resistance of System due to the Hot Electron Effect 4 Dep Var Predict Std Err Lower95% Upper95% Lower95% Upper95% Std Err Student Obs TIME Value Predict Mean Mean Predict Predict Residual Residual Residual Sum of Residuals 4.38E-13 Sum of Squared Residuals Predicted Resid SS (Press)

5 of System due to the Hot Electron Effect 5 Plot of RESID*RESIST. Legend: A = 1 obs, B = 2 obs, etc A A A A A A A A A A A A A R e A s A i A d A u a A l A A s A A A A A A A A A A NOTE: 1 obs had missing values. Resistance 5

6 of System due to the Hot Electron Effect 6 Plot of RESID*QNORM. Legend: A = 1 obs, B = 2 obs, etc A A A A A A A A A A A A A R e A s A i A d A u a A l A A s A A A A A A A A A A NOTE: 1 obs had missing values. Normal Quantiles 6

7 of System due to the Hot Electron Effect 7 Model Error Root MSE R-square Dep Mean Adj R-sq Variable DF Estimate Error Parameter=0 Prob > T Label INTERCEP Intercept RESIST Resistance Model Error Root MSE R-square Dep Mean Adj R-sq Variable DF Estimate Error Parameter=0 Prob > T Label INTERCEP Intercept RESIST Resistance RESIST Squared Resistance RESIST Model Error Root MSE R-square Dep Mean Adj R-sq NOTE: Model is not full rank. Least-squares solutions for the parameters are not unique. Some statistics will be misleading. A reported DF of 0 or B means that the estimate is biased. The following parameters have been set to 0, since the variables are a linear combination of other variables as shown. RESIST4 = * INTERCEP * RESIST * RESIST * RESIST3 Variable DF Estimate Error Parameter=0 Prob > T Label INTERCEP B Intercept RESIST B Resistance RESIST2 B Squared Resistance RESIST3 B RESIST

8 of System due to the Hot Electron Effect 10 Correlation Analysis 4 VAR Variables: RESIST RESIST2 RESIST3 RESIST4 Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum Label RESIST Resistance RESIST Squared Resistance RESIST RESIST Pearson Correlation Coefficients / Prob > R under Ho: Rho=0 / N = 31 RESIST RESIST2 RESIST3 RESIST4 RESIST Resistance RESIST Squared Resistance RESIST RESIST of System due to the Hot Electron Effect 11 Correlation Analysis 4 VAR Variables: R1 R2 R3 R4 Simple Statistics Variable N Mean Std Dev Sum Minimum Maximum R R R R E Pearson Correlation Coefficients / Prob > R under Ho: Rho=0 / N = 31 R1 R2 R3 R4 R R R R

9 of System due to the Hot Electron Effect 12 Model: MODEL1 Model Error Root MSE R-square Dep Mean Adj R-sq C.V Variable DF Estimate Error Parameter=0 Prob > T Label INTERCEP Intercept R R R of System due to the Hot Electron Effect 13 Model: MODEL1 Model Error Root MSE R-square Dep Mean Adj R-sq C.V Variable DF Estimate Error Parameter=0 Prob > T Label INTERCEP Intercept R R R R

EXST Regression Techniques Page 1. We can also test the hypothesis H :" œ 0 versus H :"

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