Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by...
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Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by the exponential model 1 fr (y; 0) e u/0; 0<y < o; 0 < 0 < 0. The station also has a spare device, so the time until this instrument is not available is the sum of these two expoential pdfs, which is 1 fr(y; 0) 2 ye "; 0<Y < oo; 0 < 0 < oo. Five data points have been collected: 9.2, 5.6, 18.4, 12.1, and 10.7. Find the maxi- mum likelihood estimate for 0. Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by the exponential model 1 fr (y; 0) e u/0; 0<y < o; 0 < 0 < 0. The station also has a spare device, so the time until this instrument is not available is the sum of these two expoential pdfs, which is 1 fr(y; 0) 2 ye "; 0<Y < oo; 0 < 0 < oo. Five data points have been collected: 9.2, 5.6, 18.4, 12.1, and 10.7. Find the maxi- mum likelihood estimate for 0. Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by the exponential model 1 fr (y; 0) e u/0; 0<y < o; 0 < 0 < 0. The station also has a spare device, so the time until this instrument is not available is the sum of these two expoential pdfs, which is 1 fr(y; 0) 2 ye "; 0<Y < oo; 0 < 0 < oo. Five data points have been collected: 9.2, 5.6, 18.4, 12.1, and 10.7. Find the maxi- mum likelihood estimate for 0. Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by the exponential model 1 fr (y; 0) e u/0; 0<y < o; 0 < 0 < 0. The station also has a spare device, so the time until this instrument is not available is the sum of these two expoential pdfs, which is 1 fr(y; 0) 2 ye "; 0<Y < oo; 0 < 0 < oo. Five data points have been collected: 9.2, 5.6, 18.4, 12.1, and 10.7. Find the maxi- mum likelihood estimate for 0. Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by the exponential model 1 fr (y; 0) e u/0; 0<y < o; 0 < 0 < 0. The station also has a spare device, so the time until this instrument is not available is the sum of these two expoential pdfs, which is 1 fr(y; 0) 2 ye "; 0<Y < oo; 0 < 0 < oo. Five data points have been collected: 9.2, 5.6, 18.4, 12.1, and 10.7. Find the maxi- mum likelihood estimate for 0. Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by the exponential model 1 fr (y; 0) e u/0; 0<y < o; 0 < 0 < 0. The station also has a spare device, so the time until this instrument is not available is the sum of these two expoential pdfs, which is 1 fr(y; 0) 2 ye "; 0<Y < oo; 0 < 0 < oo. Five data points have been collected: 9.2, 5.6, 18.4, 12.1, and 10.7. Find the maxi- mum likelihood estimate for 0. Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by the exponential model 1 fr (y; 0) e u/0; 0<y < o; 0 < 0 < 0. The station also has a spare device, so the time until this instrument is not available is the sum of these two expoential pdfs, which is 1 fr(y; 0) 2 ye "; 0<Y < oo; 0 < 0 < oo. Five data points have been collected: 9.2, 5.6, 18.4, 12.1, and 10.7. Find the maxi- mum likelihood estimate for 0. Suppose an isolated weather-reporting station has an electronic device whose time to failure is given by the exponential model 1 fr (y; 0) e u/0; 0<y < o; 0 < 0 < 0. The station also has a spare device, so the time until this instrument is not available is the sum of these two expoential pdfs, which is 1 fr(y; 0) 2 ye "; 0<Y < oo; 0 < 0 < oo. Five data points have been collected: 9.2, 5.6, 18.4, 12.1, and 10.7. Find the maxi- mum likelihood estimate for 0.
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